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_CHANG & ENG_ is a Singaporean musical theatre production directed by Ekachai Uekrongtham based on the lives of the Siamese twins, Chang and Eng Bunker. The music and lyrics were by Ken Low, with the book by Ming Wong, costumes by Niphon Tuntiyothin, set design by Thoranisorn Pitikul, lighting by Thio Lay Hoon, orchestral arrangement by Iskandar Ismail and choral direction by Babes Condes. The musical was first performed in 1997, rerun in subsequent years until 2002 and has since travelled around Asia. Performers such as RJ Rosales, Robin Goh and Edmund Toh have been cast as Chang and Eng, and writer-composer Ken Low has a cameo as the King of Siam in some productions.

Chang and Eng also became the first English Language Musical to be performed in the People's Republic of China between 9th - 11 December 1997 at the Century Theatre, Beijing.

The musical focuses on the lives of Chang and Eng, from their troubled childhood, seen as outcasts by children in Siam but reassured by their mother Nok, to their journey to New York as exhibits managed by Captain Abel Coffin and their settling down with Adelaide and Sallie Yates in North Carolina.

Major characters

-   CHANG (tenor/baritone) - one half of the conjoined twins and the more optimistic and confident of the two
-   ENG (tenor/baritone) - the other brother and the more moody of the two, dependent on his more confident twin for support
-   NOK (mezzo-soprano)- the twins' mother who helps them to cope with the mockery and rejection of their peers
-   CAPTAIN ABEL COFFIN (tenor/baritone) - The opportunistic American merchant who takes the twins to exhibit them in New York
-   ADELAIDE YATES (mezzo-soprano) - One of the two Yates sisters who goes on to fall in love with and later marry Chang
-   SALLIE YATES (mezzo-soprano) - the other Yates sister who falls in love and later marries Eng
-   KING RAMA III (baritone) - the King of Siam
-   MIDWIFE (mezzo-soprano) - the “Grand Midwife of the West” who delivers the 21 children of the twins' wives.

Synopsis

ACT 1

The musical begins in New York, 1829 where curious crowds gather to witness a public display of Chang and Eng, the Siamese twins joined at the chest (Eighth Wonder of the World). The twins' manager, Captain Abel Coffin, lures the crowds in as he prepares to unveil the exhibit, billed as the Eight Wonder of the World, for the first time. Backstage, before the exhibition, the twins discuss their future in America, Chang with visions of grandeur and Eng with apprehension (From Now On).

We are then transported to the twins' childhood in Siam, 1819. At the age of eight, Young Chang and Young Eng are two healthy boys who have managed to adapt to living as conjoined twins. However, they are constantly mocked by other children and not accepted by them (Stuck Together). As a severe cholera epidemic breaks out in Siam, the twins are denounced as an evil omen. The twins' mother Nok continues to love, protect and reassure Chang and Eng through their difficulties (Mai Phen Rai (Never Mind)).

Ten years later, Chang and Eng have become shrewd teenage businessmen, selling duck eggs to provide for their family. Their lives take an unexpected turn when they are summoned to appear before the King Rama III of Siam in the Royal Palace who is delighted to meet them and sends them as envoys to the Kingdom of Cochin China (Pride and Joy).

By this time, they have caught the attention of Captain Abel Coffin, an opportunistic American merchant who takes them to America, leaving behind their home and their mother.

ACT 2

The day after the exhibition, paper boys crowd the streets of New York with breaking news about the Siamese Twins' arrival, their exhibition and speculation about whether or not they are a hoax (Read All About It). Coffin offers free shows to prove the twins are not a hoax, and as part of his publicity plan has the twins examined by a team of prominent surgeons in order to have the twins' condition authenticated and for the doctors to see whether separation is an option (How Extraordinary).

ACT 3

Act 3 opens when the twins declare their independence from Captain Coffin to be their own men. In 1840, they quit going on exhibit and settle down in North Carolina to lead a normal life. They become naturalized U.S. citizens, adopting Bunker as their new surname. They meet two sisters, Sallie and Adelaide Yates, at a garden wedding reception. Afterwards, both sisters find themselves drawn to the twins and share their feelings with each other (Four Could Be Heavenly). Facing opposition for their relationships (Chang with Adelaide and Eng with Sallie), they decide to let it run its course (Maybe it Needs a Little Time). Consumed by their feelings for the sisters, Chang and Eng begin to yearn for lives apart (If Only). However, they finally settle down, and before long the sisters are pregnant with the children of the twins (The Grand Midwife of the West).

However, as the twins get older, their personality differences deepen and their desire to lead separate lives grows stronger. This is worsened by the domestic quarrels between their wives and children. In the meantime, The American Civil War looms in the background as the tension between the northern and southern states intensifies (Divided). At the end of the Civil War, Chang and Eng find themselves stricken by poverty and unwillingly return to make public appearances to support their large family. The musical ends with the twins near-death, reminiscing about the words their mother told them as children (Mai Phen Rai (Never Mind) Reprise).

Main Actors (Beijing Performance)

-   Chang Bunker: Edmund Toh
-   Eng Bunker: Jeremy Sing Seng Kwang
-   Nok: Selena Tan
-   Adelaide Yates: Pippa Birkbeck
-   Sallie Yates: Mary-Anne McCormack
-   Coffin: Patrick Gallo
-   King of Siam: Ken Low

Song List

Act One

-   Eighth Wonder Of The World
-   From Now On
-   Stuck Together
-   Mai Phen Rai (Never Mind)
-   Royal Thai Dance (Instrumental)
-   Pride & Joy

Act Two

-   Read All About It
-   How Extraordinary!

Act Three

-   (Four Could Be) Heavenly
-   Maybe It Just Needs A Little Time
-   If Only
-   The Grand Midwife Of The West
-   Divided
-   Mai Phen Rai (Never Mind) Reprise

Category:Singaporean musicals Category:1997 musicals

title: Chang & Eng

question: Describe the major characters that are in the musical.

answer: The major characters in the musical each have their own personality and role. Chang, who is a tenor/baritone, is one of the half of the conjoined twins and is optimistic and confident. Nok is a mezzo-soprano, and is the twin's mother and helps them cope with the mockery and rejection of the twin's peer. Adelaide Yates, a mezzo-soprano, is one of the two Yates sister who falls in love with Chang and marries him. There is also a midwife, a mezzo-soprano, who delivers 21 children of the twins' wives. All character in the musical have their own role and story.

question: Describe what fueled the twins desire to lead separate lives.

answer: Being conjoined at the hip did create problems for the twins as they grew older. The twins fell in love with a set of sisters and wanted to be able to live their lives apart with their wives. Additionally, as the twins got older, they had more personality differences which added to their desire to lead separate lives. And because of these personality differences, there were more quarrels between their wives and children.

question: How popular and successful was this Singaporean musical theatre production?


split: train

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cacy and safety to receive a Food and Drug Administration (FDA) license [1]. Such high rates of discordance between preclinical reports and clinical effects have prompted mounting scrutiny of the design, reporting, and reproducibility of preclinical research.

Being unable to reproduce preclinical findings can impede medical progress and misallocate intellectual capital. For example, laboratories attempting to reproduce original findings might squander limited research resources because they are not attuned to subtle techniques needed to reproduce an original finding. Of even greater concern is the prospect of launching clinical investigations on the backs of invalid preclinical reports. Scientists’ judgments about an experiment’s reproducibility influence how they go about designing similar studies, as well as which findings are utilized for the design of subsequent studies. Accurate judgment about reproducibility therefore affects how efficiently science self-corrects.

There is widespread debate about the scope of the reproducibility problem in many scientific fields, including biomedical research. Most scientists (52%) think there is a “significant” reproducibility crisis, whereas the remainder think there is, at worst, a “slight” crisis [2]. Some direct efforts at reproducing preclinical and basic science findings have suggested that many original findings may be spurious. For example, researchers at Amgen were unable to reproduce 89% of cancer preclinical studies provided to them by academic scientists; similar challenges were reported by Bayer scientists [3]. However, community-wide beliefs are somewhat measured, since 31% of researchers believe a result still might be true even in light of a failed replication attempt [2]. Indeed, many commentators have questioned the efforts and expertise of those conducting replication studies [4,5]. Uncertainty about the extent, causes, and impact of the “reproducibility crisis” has led to calls for more systematic assessments of the problem [6]. The Reproducibility Project: Cancer Biology (RP:CB) is currently conducting 29 direct replication studies to evaluate the replication rate in cancer biology [7].

By collecting subjective probability forecasts on outcomes that can be unambiguously dichotomized, one can score the accuracy of individuals’ strength of belief using well-established methods from the decision sciences [8]. For example, in a study examining economists’ predictive judgments about replication studies, forecasts significantly correlated with replication results and beat a matched prediction market about the same replication studies [9]. In contrast, psychologists’ forecasts did not significantly correlate with replication results, and their forecasts were beaten by a similar, matched prediction market [10].

Here, we report forecasts and their accuracy for the first 6 mouse-model replication studies conducted by the RP:CB. We set out primarily to determine the extent to which expert cancer researchers can accurately predict the probability of replicating significance levels and effect sizes from specific original studies in the RP:CB. We close by discussing our findings in light of the many complexities of conducting and interpreting replication studies, including the particular experiments used in our surveys.

Results

Sample demographics

We recruited a sample of 196 participants, including 138 experts and 58 novices, to perform forecasts for our study (Table 1 summarizes the sample demographics). Experts were predominantly male, whereas there were slightly more female than male novices. Our expert sample showed a somewhat lower mean h-index compared with nonresponders (25.6 versus 32.4)—based on an equally sized random sample of nonresponders.

The average expert had published 89.5 (SD = 109.0) papers and been cited 4,546.1 (SD = 7,932.4) times. A third of the sample (27% of experts and 44% of novices) had not heard of the RP:CB, while 9% (10% of experts and 7% of novices) were actively awaiting results. The expert sample believed they had reasonable expertise pertaining to the studies in our survey. The mean expertise rating was 4.2 (SD = 1.9) on a 7-point scale (with 1 representing minimal expertise and 7 representing maximal expertise). A plurality of expert participants (45%) rated their expertise above the scale’s midpoint, and 33% below the midpoint. The mean expertise rating for the novices was 2.9 (SD = 1.5), with only 15% of novice expertise ratings above the midpoint and 65% below. Both the experts and novices rated high confidence in their forecasts, 77% versus 76% respectively. For both groups, 84% of confidence ratings were above 50%, and only 3% were below.

Table 2 shows the publications used in this forecasting study and summaries of forecasts for each [11–16]. Disease indications in xenograft studies included prostate, lung, renal cell, and breast cancer, as well as myeloma, leukemia, and melanoma, and the experiments used a variety of outcome measures, including disease-free survival, tumor weight and volume, organic phase absorbance, and bioluminescence. Studies were preselected by the RP:CB using a standardized search method [7].

Forecast properties

Experts used the whole spectrum of belief (see Fig 1). They tended to believe replication studies would demonstrate statistical significance, since 73% of forecasts were above 50%, and 49% were above 75%. Only 18% of forecasts were below 50%. In contrast, experts gave lower forecasts (centered near 50%) for effect size, with forecast patterns suggesting community uncertainty (median forecast of 50% for 4 studies and the other 2 suggesting doubt (median forecasts of 25% and 40%).

[thumbnail]

Fig 1. Expert forecasts by identified expertise and by study.

The gray histogram represents the forecasts of significance (panel A) and effect size (panel B) with bins of 5%. A 100% forecast and a 0% forecast would indicate certainty that an event will occur and will not occur, respectively; 50% would indicate maximum uncertainty. The red lines represent forecasts for the studies in which each forecaster was identified during sampling via either citations or a “similar articles” search (“identified expertise”). The blue lines represent the forecasts made by experts on studies that did not lead to their identification in sampling (“general expertise”). The lower panels are violin (probability density) plots for each outcome type (panel C for significance and panel D for effect size) and each study by both identified (in red) and general (in blue) expertise. Box plots are contained within each violin plot.

https://doi.org/10.1371/journal.pbio.2002212.g001

Our question about effect sizes could be interpreted differently, resulting in high variability in forecasts. To corroborate interpretation of effect size forecasts, we asked forecasters the likelihood of a perfect replication study producing effect sizes as large or larger than the original, if an original finding were reproducible. We then compared these figures with an individual’s forecasts (see S3 Fig in the Supporting Information). A total of 17% of experts offered forecasts equal to their idealized replication, while 56% provided forecasts that were lower than their ideal, suggesting a degree of doubt about these studies and/or the RP:CB methods.

Forecast accuracy

None of the 5 reproducibility studies in our survey successfully replicated the original studies using either significance or effect-size criteria [17–21]. Thus, accurate forecasting would require a strongly pessimistic response pattern. Table 3 displays experts’ forecast accuracy by outcome and expertise types. Experts were extremely overconfident about the replication rate, especially for significance. The specificity of all expert forecasts was 0.39, meaning 39% of forecasts (excluding fence-sitting 50% forecasts) were in the correct direction. The specificity of significance forecasts was 0.20, showing that the experts were substantially overoptimistic about significance replicability. The specificity of effect size forecasts was better, 0.64. Therefore, experts were more accurate (and pessimistic) about the replicability of effect sizes than significance levels.

Forecasters’ mean Brier score was 0.40, 95% CI (0.38–0.45), indicating forecasting skill was significantly worse in our expert sample than guessing 50% each time (the latter would have generated a Brier score of 0.25) (see Fig 2). A fifth of experts (21%) had mean Brier scores less than 0.25. Among experts, Brier scores were worse for significance than for effect-size forecasts (median = 0.58 and 0.25, respectively), with 11% of experts scoring better than 0.25 (4% for significance forecasts and 30% for effect-size forecasts).

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Fig 2. Brier scores by outcome type with sensitivity analysis.

The gray histograms display Brier scores for the 5 studies with known results. All experts are displayed in panel A, and they are divided by outcome types in the bottom panels (B for significance and C for effect size). The green lines represent the probability density of Brier scores if the sixth study replicates each outcome, and the red line represents if it fails to replicate for each.

https://doi.org/10.1371/journal.pbio.2002212.g002

Factors associated with greater forecasting skill

A possible explanation for low Brier scores is that forecasters might have lacked expertise in the specific studies in our sample. We probed the relationship between expertise and forecasting skill in several ways.

First, we tested whether forecasters performed better on the studies for which we had identified them as experts. Forecasts with identified expertise were more likely to use high extreme values (63% of forecasts were ≥ 75% compared to 51% with general expertise, a difference of 12%, 95% CI [0.02 to 0.22]) and less likely to give forecasts near the low extreme (8% of forecasts were ≤ 25% compared to 15% with general expertise, a difference of 7%, 95% CI [−0.13 to −0.002]), suggesting greater optimism about reproducibility in one’s own research area. The mean Brier score for significance forecasts was marginally greater for identified expertise (0.61, 95% CI [0.54 to 0.66]) than for general expertise (0.52, 95% CI [0.49 to 0.58] for a mean difference of 0.09, 95% CI [−0.01 to 0.15]). Effect-size forecasts centered around 50% (in terms of median and mode) for both identified and general expertise. Forecasts from general expertise were more likely to use extreme low values: 36% of forecasts in the lowest quartile compared to 27% for identified expertise (a difference of 9%, 95% CI [−0.01 to 0.18]). Experts performed better when they were not identified as having expertise, possibly indicating that experts are overconfident when they are more knowledgeable and/or more doubtful about others’ research.

A second way we probed the relationship between expertise and forecasting skill was by comparing experts to a sample of trainees in competitive molecular biology programs. We reasoned that if experts outperformed novices, then forecasting success is associated with expertise; if novices outperformed experts, then there is evidence that expertise is associated with overconfidence. We observed the same general patterns of (a) optimism for significance forecasts and (b) uncertainty for effect-size forecasts (centered around a mode of 50%) with a pessimistic leaning (a local mode at 10%) (see S2 Fig in the Supporting Information for a comparison of expert and novice forecasts). Overall performance did not favor either group: experts slightly outperformed novices in accuracy (median Brier = 0.32 versus 0.35), but novices slightly outperformed experts in specificity (0.45 versus 0.43). Experts’ significance forecasts were significantly more accurate (mean Brier score 0.43, 95% CI [0.38 to 0.49]) as compared with novices (mean = 0.51, 95% CI [0.48 to 0.60] for a mean difference of 0.08, 95% CI [−0.18 to −0.02]) and showed better specificity (0.30 versus 0.24). Experts were more pessimistic (i.e., more likely to offer extremely low forecasts and less likely to use extremely high forecasts). We observed the opposite pattern for effect-size forecasts. Median Brier scores (0.17 versus 0.25) and specificity (0.68 versus 0.59) for novices beat experts.

We also explored the relationship between 4 expert/forecast characteristics and skill scores: confidence in their forecasts, expertise, age, and h-index (the former 3 were self-reported; see Fig 3). The most notable impacts on the forecasts were confidence (r = 0.20, _p_ < 0.01) and h-index (r = −0.15, _p_ < 0.01). High confidence was indicative of poor accuracy, since mean Brier scores increased (r = 0.36, p < 0.01 for significance forecasts) and specificity decreased as confidence increased for both outcomes. For effect sizes, low confidence was associated with greater fifty-fifty forecasting, whereas high confidence led to greater variability in the forecasts. Specificity and accuracy improved with h-index for both outcome types. For significance, higher h-indices were associated with pessimistic, and thus more accurate, forecasts (r = −0.18, _p_ < 0.01). For effect sizes, a low h-index was associated with a high degree of fifty-fifty forecasting, and a high h-index was associated with lower forecasts (r = −0.15, _p_ < 0.01). In fact, experts with a high h-index did better than “fence-sitting,” with a mean Brier score of 0.17 and specificity of 0.81. When comparing expertise measures, experts were more accurate when they had general, compared to identified, expertise across h-index levels. The third of experts with the lowest h-indices were more discrepant, as Brier scores decreased by 0.09 on average when they had identified expertise, whereas the decrease was only 0.03 for the other two-thirds of experts.

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Fig 3. Forecasts and Brier scores by discretized predictors.

All graphs show violin plots with embedded box plots and medians. Panels A and B display forecasts and Brier scores, respectively. Top and bottom rows show results for significance and effect-size forecasting, respectively. The columns show 4 predictors: self-reported confidence, self-reported expertise, age, and h-index (i.e., mean indices obtained from Scopus and Web of Science). Predictors were trichotomized to give approximately equal group sizes.

https://doi.org/10.1371/journal.pbio.2002212.g003

Finally, we explored whether gender showed a relationship with forecasts and accuracy. Female experts gave forecasts that were about 8% higher on average than their male counterparts for both significance and effect size; female novices’ forecasts were about 6% higher on average than males for both. As a result, females’ Brier scores were higher than males’ both on replicability of significance (mean Brier score = 0.48, 95% CI (0.42 to 0.66) versus mean Brier score = 0.42, 95% CI [0.35 to 0.47]) and effect size (mean Brier score = 0.32, 95% CI [0.21 to 0.46] versus mean Brier score = 0.25, 95% CI [0.20 to 0.30]). Novice females also were less accurate than their male counterparts on significance replicability (mean Brier score = 0.56, 95% CI [0.50 to 0.67] versus mean Brier score = 0.46, 95% CI [0.41 to 0.66]) and effect size (mean Brier score = 0.28, 95% CI [0.21 to 0.39]) versus mean Brier score = 0.22, 95% CI [0.16 to 0.34]). The gender difference for replicability of effect-size forecasts was significant for both experts (0.07, 95% CI [−0.24 to −0.02]) and novices (0.06, 95% CI [−0.18 to −0.07]).

Sensitivity analysis

The results from Study 29 have not yet been revealed. We performed a sensitivity analysis to determine how the results would change contingent on the eventual results of that study. The sensitivity results are shown in Figs 2 and 3 and S5 Table in the Supporting Information. Significance forecasts for Study 29 were less optimistic (median of 75%), and effect size forecasts were more pessimistic (median of 40%) than all but 1 of the other studies.

Overall, Brier scores will improve regardless of whether Study 29 reproduces the original effect. However, potential gains would be modest and would still underperform a fence-sitting strategy (Brier score = 0.25): If RP:CB results replicate Study 29, the overall mean Brier score would improve from 0.41 to 0.38, whereas if RP:CB does not replicate Study 29, it would be 0.40. If RP:CB replicates the results of Study 29, the mean Brier score for significance forecasts would improve significantly from a mean of 0.57 to 0.48 (95% CI [0.45 to 0.51]) and would show less improvement if Study 29 does not replicate, to 0.54 (95% CI [0.50 to 0.58]). The change for effect size forecasts would be smaller, but a positive replication would make the mean Brier score worse, from 0.26 to 0.29 (95% CI [0.26 to 0.32]), and a nonreplication would improve it to as good as a fence-sitting strategy (0.25, 95% CI [0.18 to 0.25]). All of the changes would be significantly different from the current results.

Discussion

Our findings suggest that, on average, preclinical cancer researchers are overly optimistic in their beliefs about reproducibility. Half of all expert forecasts indicated that the replications were more likely to replicate original results than not, whereas only one-third indicated greater likelihood of replication failure. Overconfidence in reproducibility of specific results was particularly prevalent in significance forecasts, where 73% of expert forecasts favored successful replications. Forecasters were less certain (and more pessimistic) about replicating effect sizes.

There are several ways of interpreting our findings. Perhaps the most direct interpretation is that researchers consistently overestimated the validity of original reports. The high degree of optimism about statistical significance might reflect that experts believe effects in original studies are “real” (hence, they believe the replication results will also be positive and significant) but question the magnitude of treatment effects (hence, they show less optimism about effect sizes). Researchers may interpret the original significance levels as strong evidence that the effects are true positives, while they are more open to the possibility of type M (magnitude) error—which should be expected when samples sizes are small and/or measurements are noisy [22]. This interpretation implies researchers believe published results tend to be qualitatively valid but consistently overestimate effect sizes.

A second interpretation of our findings is that researchers were overly optimistic about the ease with which the original methods could be accurately replicated by independent laboratories or, more specifically, about the ability of these replicating laboratories to perform these particular replication studies [23]. RP:CB authors have stated that obtaining original protocols and materials was challenging, and originating labs often had to reconstruct materials that were unavailable [24]. Since publication of the first RP:CB studies, there has been a vigorous discussion about whether replication attempts were faithful to original methods, especially since 2 of the replication studies were deemed uninterpretable [25]. The RP:CB methods have been criticized for being too rigidly constrained by their registered protocols, preventing adjustment to challenges that arose while implementing original protocols [24–26]. Xenograft studies—which were the focus of our forecasting exercise—have come under particular criticism [25]. The 2 RP:CB replication studies that have received the most methodological criticisms had the second and third highest mean forecasts of significance. This suggests experts could have been overly optimistic about the challenge of executing direct replications in living biological systems or about the specialized skills RP:CB researchers would need to implement novel techniques.

A third interpretation is that forecasters were wrong in the specifics but right in the generalities. It is possible in each case that the original study was an overestimate of the effect size and the replication was an underestimate. As a consequence, further effort at replication might ultimately vindicate the experiments that did not successfully recapitulate effects observed in the original study. However, it is unlikely we would see the same pattern with such stark contrasts for every study. A different version of this interpretation is that some participants responded to our forecast questions with their beliefs about the underlying biological claims, rather than instantiations of them in particular laboratory experiments. In response, we point out that 2 of the 5 studies in our survey (19 and 21) were widely reported as having confirmed underlying biological claims, while 1 of the studies (15) was reported as having been disconfirmed [25]. If forecasts were right in the generalities, we would expect forecasts to be consistently higher for 19 and 21 than for 15 for both measures of replication. As Fig 1 shows, forecasts were pessimistic for Study 21 and relatively moderate for Study 15.

Although our study was not designed to discriminate between these various interpretations, it raises important questions about the way expert researchers interpret the sorts of high-impact findings tested in RP:CB. We find that biomedical scientists are inclined to overestimate the validity of original reports and/or underestimate the difficulty in conducting direct replications. The latter would perhaps be of less concern for science policy than the former. However, inability to appreciate the sensitivity of original reports to subtle laboratory conditions or aleatory uncertainty can result in potentially unfruitful debates about reproducibility, as well as wasted efforts as laboratories vainly attempt to follow protocols in original reports. It is beyond the scope of this paper to discuss the quality and reliability of experiments employed by the RP:CB. Scientific reports and news coverage of RP:CB have highlighted the difficulties in implementing replication studies (e.g., the commentaries reacting to the RP:CB results in _eLife_, _Nature_, and _Science_). We make no claim here about whether or not the RP:CB studies we examined constitute a gold standard of replication. We merely note that the manner in which such questions are resolved has implications for the interpretation of our results. Nevertheless, if—as many critics suggest—RP:CB experiments inadequately implemented original methods, our findings do not suggest these failings were apparent to our participants.

If forecasting improved with expertise, then some risks of overconfidence might be mitigated. Elsewhere, experts have been found to be as overconfident as novices, and the relationship between expertise and predictive skill is complex and task dependent [27,28]. In our study, greater topic expertise did not improve forecasting: indeed, experts displayed greater overconfidence when they were more familiar with a study and in general did not outperform our sample of trainees. This might be explained by experts having a tendency to take the “inside view”—a focus on the unique details of each specific experiment—over the “outside view”—a focus on the class of similar events [29]. The outside view tends to beat the inside view in predictive judgments [30]. On the other hand, our observations hint at the prospect that greater researcher impact (as measured by h-index) was associated with more accurate forecasts. Some reasons to expect experts to outperform nonexperts are they search for fewer total but more diagnostic cues and rely more on their existing knowledge and strategies [31].

We urge caution interpreting our results since reproducibility is difficult to define and measure [32]. Our survey scored forecasts using common forecasting methods that dichotomize whether studies reproduce based on 2 different criteria (significance and effect size). A strength of this method is that it creates predictive judgments that are verifiable. Participants’ judgments do not represent participants’ comprehensive beliefs about the treatment mechanisms at hand. However, it is rarely possible to capture such judgments in a manner that can be verified in a timely fashion. We do not suggest the forecasts collected in our study reflect judgments concerning fundamental scientific relationships generalized beyond the context in which they are tested. Additionally, replication is not an “all or nothing” phenomenon; 2 replication studies failed to reproduce statistical significance and had greatly diminished effect sizes but nevertheless showed effects that—when meta-analyzed with the original report—excluded the null hypothesis. Therefore, interpreting the overall success of these replications is to some degree in the eye of beholder. Moreover, a failed replication is not the same as evidence that the effect does not exist. However, there is no prescribed degree of disparity from an original result that is considered tolerable [33]. If the original and replication studies were sound methodologically, it can be difficult to judge if the original study overestimated or if the replication underestimated a true effect [34].

Our findings are subject to several limitations. First, despite a vigorous recruitment effort, our response rate was probably low, and our bounce rate was high. This may reflect some controversy surrounding the RP:CB. Nevertheless, we were able to capture a meaningful sample of experts: 138; this figure compares favorably with other studies requiring esoteric, expert research participants. The mean h-index for responders was somewhat lower than for nonresponders, suggesting our participants may have been slightly younger or marginally less productive than our sample population. However, the upper third of our sample had a high h-index (49.1 on average compared to 32.4 for the average nonresponder), including 22 experts with h-indices exceeding 40. Second, the gender imbalance in our expert sample is notably larger than in our novice sample. This imbalance may reflect an inherent gender imbalance between senior and junior researchers. Experts in life sciences tend to be primarily male (for example, 25% of tenured faculty positions in the biological and life sciences were held by females in 2013 [35]), while trainees tend be more female (for example, 53% of biological doctorates were awarded to women that year [36]). Females’ forecasts were about 6% higher on average, but the overall patterns of optimism held across gender. Third, our sample of experiments was small, and there was no variability in the reported results. We selected xenograft experiments because they are generally regarded as more predictive of clinical utility and the results were verifiable; this choice limited the number of available studies. We selected experiments a priori without any knowledge of outcomes, and the lack of variability in outcomes ultimately limited our ability to test researchers’ capacity to discriminate between studies that reproduce from those that do not. Our findings should therefore be replicated in a larger sample of experiments before drawing conclusions about the forecasting skill of cancer biology experts. Fourth, we do not know what the forecasters were intending to communicate when they offered forecasts. Forecast methods do not account for forecaster motivation. Indeed, the use of a “proper scoring rule” is intended to incentivize truthful—as opposed to strategic or motivated—disclosure of belief. Nevertheless, forecasters could have intended optimistic forecasts as a way of portraying the field positively or defending it against skepticism. Paradoxically, participants may have intended to express relative pessimism about reproducibility, since forecasts tended to be lower than participants’ expectations about perfectly reproducible effects (see S3 Fig in the Supporting Information). Such pessimistic forecasts could be a hedge so that the cancer field in general would appear better than predicted if replication results were “positive.” In any event, unconscious motives often play a role in survey responses and cannot be excluded as an explanation for the observed patterns. Fifth, our surveys assumed a certain amount of statistical knowledge. For example, asking individuals whether replication studies would achieve statistical significance (_p_ ≤ 0.05) requires understanding what a _p_-value measures. We regard this as a potential strength, however. Scientific reports routinely convey claims through metrics like _p_-values or standardized mean differences. Therefore, the ability to derive valid inferences from such metrics is integral to forming judgments about effects and reproducibility.

Expert predictive judgment in biomedical research has not, to our knowledge, been previously studied. Scientists tend to focus on finding physical truths, and discrepancies between results often trigger debate about the methods used in each study. We suggest the role of scientific judgment is also important because physical truths can never be proven with certainty. The judgment of experts thus determines—at least in the short term—the way discrepant results are interpreted and which findings are taken as fact. Our study provides evidence that community-wide judgments about reproducibility are overoptimistic and overconfident.

The assessment and cultivation of researcher judgments, we suggest, may lead to a more efficient research enterprise. Knowing how well biomedical researchers can predict experimental outcomes is crucial for maintaining research systems that set appropriate research priorities, that self-correct, and that incorporate valid evidence into policy making. Regardless of how one interprets our results, these findings have potential policy implications, since they suggest that biomedical scientists have a difficult time anticipating outcomes when high-impact experiments are repeated. We believe it would be valuable to work to improve the judgments of researchers and trainees. There are common traits of domains in which experts’ forecasts tend to be more accurate and discriminating. Judgments must be formally quantified, and feedback should be timely, as unambiguous as possible, and easily compared to the original forecast [37]. Forecasting skill may also be better in domains in which expert judges are directly accountable to skeptical constituencies for the quality of their predictions [38]. We cannot expect researcher judgments to improve until the proper structure is in place to help them succeed.

Methods

Ethics statement

Human participant procedures were approved by the McGill University Faculty of Medicine Institutional Review Board (Protocol #A01-B05-16A). Each participant provided informed consent before commencing.

Participants

We recruited experts using a 2-pronged search for authors of publications related to the first 6 studies in RP:CP (a flow chart of the sampling process is shown in S1 Fig in the Supporting Information). First, we used SCOPUS to identify all papers citing each original study. Second, we performed a “similar articles” search of each original study using PubMed. Both searches were conducted between February and July 2015. We captured the identity of all authors of the obtained articles. Individuals were eligible as experts if (a) they were named as a corresponding author on any article captured in our 2 searches or (b) their name appeared 3 times, in any author position, in 1 of the searches. Eligible experts were sent up to 5 email invitations spaced at least 1 week apart or until an invitee completed the survey or actively declined.

As a comparator, we also created a sample of biomedicine novices by circulating survey invitations to all graduate and postdoctoral students in programs with relevant cancer training at 2 leading research universities—1 in eastern Canada and 1 in the northeast United States. Use of such a comparator was prompted by the observation that experts in other fields sometimes underperform nonexperts when making predictive judgments [39,40]. We incentivized invitees by offering a C$200 reward to the top 2 forecasters and C$50 to the 2 next best forecasters. We also offered the top 3 forecasters the option of having their names published at http://www.translationalethics.com/forecast-scoreboard/.

A total of 2,667 experts were invited to participate: 12.3% (329) of invitations bounced, and 1.57% (42) actively declined. Assuming that all nonbounced invitations sent were actually received by our targets, 6% (138) of invited experts forecasted at least 1 study. Because novice invites were circulated by graduate program directors, we cannot calculate response rates for novices. We excluded the data of 1 participant who completed the survey well below our threshold of 7 minutes. We disqualified 12 forecasts for which participants declared knowledge of the replication results.

Surveys

We based our queries of reproducibility on mouse tumor growth curves in the first 6 studies planned by RP:CB. We used mouse xenograft experiments because they are believed by many to be the most prognostic of clinical utility. Ideally, we would solicit subjective probabilities (i.e., forecasts) on whether whole studies reproduced. However, every study contained multiple experiments, and the definition of “reproduction” is itself highly debated [32,33]. As a result, using such an approach would make it impossible to verify the accuracy of forecasts. Instead, we used an approach that minimized the interpretational ambiguity of our questions and the ensuing forecast data. Each experiment had a single effect (treatment versus control) that could be said to represent the main finding of the study. This allowed us to collect predictive judgments for each study and to create objective and unambiguous methods for scoring each prediction. To maintain a mean survey duration of 30 minutes, we created 2 batches of surveys, each asking about 3 RP:CB studies. Survey questions were reviewed and approved by cancer preclinical researcher consultants.

For each replication forecast, we gave participants the study title, authors, and links to both the original study and the registered report for the replication. We also gave them the relevant figure from the original paper, with annotations indicating the effect our query centered on. Participants were asked to indicate their subjective probabilities (in percent chance format) that (a) the replication experiments would “also be statistically significant in the same direction (as the original study)” and (b) the effect size of the replication would be “as large or larger than the original effect size.” We chose these particular questions over more complicated judgments to minimize the degree to which our findings would be confounded by participants’ statistical sophistication [7,32,41].

For secondary analyses, we probed (a) confidence in each forecast, (b) self-rated expertise on each experiment, (c) additional cognitive variables shown to correlate with forecast skill in other domains: actively openminded thinking [42] and belief in the progress of medical research-adapted from an economic boomster-doomster scale [43], and (d) questions about their familiarity with and the anticipated influence of the RP:CB on how they read papers and design studies. We also asked participants to estimate the overall replication rate the RP:CB will report, but we do not present this data in the current paper since it is premature to do so, and we do not want to confuse researchers’ beliefs about xenograft studies with their beliefs about in vitro studies. Participants were also asked the following: “Imagine a replication study perfectly reproduces the effects observed in an original study. How likely would the effect be as large or larger than that provided in the original study?” We provided an open text screen for respondents to provide thoughts and feedback on our survey. Further details, including the study protocol, are provided in the Supporting Information (see S1 Text). Surveys were conducted online using Surveymonkey. The order of studies in each survey was drawn randomly for each participant.

We analyzed the results of the first 5 studies whose outcomes are resolved and that have been published in _eLife_ [17–21], and we present a sensitivity analysis of the sixth study by describing how the forecast results would change if it replicated the results or not. Accuracy of forecasts were calculated using the Brier score, a proper scoring rule for forecast accuracy that measures the squared deviation between a forecast probability and the actual outcome (coded 0 for nonoccurrence and 1 for occurrence) [44,45], so a lower Brier score denotes a more accurate forecaster than a higher score. A forecaster who behaves like a clairvoyant, correctly classifying all outcomes with complete confidence, would get a perfect Brier score of 0. In contrast, a forecaster who invariably guesses 50%—a common response for participants who do not know how to answer questions about the probability of binary options, sometimes called “the fifty-fifty blip” [46]—would have a Brier score of 0.25. We report mean Brier scores with bias-corrected 95% bootstrap confidence intervals with 5,000 resamples. All hypothesis tests were conducted using bootstrap t-tests based on whether 95% bootstrap confidence intervals of the mean difference contained the value 0. We also report the extent to which forecasts correctly identified which studies would not replicate using specificity (i.e., the “true negative rate”), which is normalized by the sum of true negative and false positive forecasts. Data analysis was conducted using R statistical software.

Supporting information

S2 Fig.Direct comparison of forecasts and Brier scores by rank for survey 1.

The first row shows forecasts and the second shows brier scores. The first column shows significance and the second shows effect size. For each panel, the histogram is the aggregate as all of respondents, the red line is for experts and the blue line is for novices.

https://doi.org/10.1371/journal.pbio.2002212.s002

(TIF)

S3 Fig.Likelihood of reproducing upon perfect replication.

In the top row, the dark gray histograms show the forecast of a (genericized) perfect replication, and density lines show actual effect size forecasts. The bottom row is the perfect replication ratio: log(forecast/perfect replication). Thus, a negative value indicates the forecast is lower than the perfect replication. The left column shows data from all experts, whereas the right column shows survey 1 data comparing experts to novices. There are multiple interpretations of the idea of a perfect replication. 1) The modal response was .5, which may indicate that the original effect size is a reasonable estimate of the true effect; 2) some participants thought it should be high (.95 for students; 1 for novices), perhaps based on the possibility of Type I error from the original study; 3) some participants expected .8, perhaps based on the power and Type II error from the replication study; 4) and yet others thought it was less than 50% (20% or 30%), suggesting they may have a cynical view of reproducibility in this field. There is a strong peak in panels 3 and 4 for participants who made forecasts in line with a perfect replication. Beyond that, the trend is to make forecasts below a hypothetical perfect replication, so the forecasters were consistently acknowledging that real replication studies are flawed to some degree. Experts were more likely than novices to forecast higher than the perfect replication seemingly suggesting that some of these replication studies were highly likely to replicate the original results compared to other studies.

https://doi.org/10.1371/journal.pbio.2002212.s003

(TIF)

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question: Why are their high rates of discordance between preclinical reports and clinical effects?

answer: The study finds that it could be because preclinical cancer researchers are overly optimistic and overly confident in their beliefs about reproducibility.

question: Why were researchers at Amgen unable to reproduce 89% of cancer preclinical studies provided to them by academic scientists?

answer: The studies that were being reproduced could be false.

question: Briefly describe the "reproducibility crisis".

answer: It is the high rate of discordance between preclinical reports and clinical effects that is creating scrutiny of the design, reporting, and reproducibility of preclinical research.

question: Summarize the first interpretation of the findings in the discussion section.

answer: Researchers consistently overestimated the validity of original and public reports and effect sizes.

question: How might a high degree of optimism about statistical significance affect expert's studies?

answer: Researchers may interpret the effects in their replicated studies as significant and positive.


text:
	"I'm feeling it again," Kiasha gasped to her husband in a panicked voice. "I'm tellin' you, this don't feel like no kicking, Deandré."
"Bullshit!" Deandré spat at his pregnant, teary-eyed wife, who was now backing up into a corner of their living room in fear of getting beaten by her husband. Domestic violence was a casualty in this household.
'"If only you believed me! If only you could fell what I feel!" Kiasha whispered.
"Woman, I don't give two shits what you feel! We gettin' a divorce and that's my final word on the matter! Ain't nothin' you can say to change my mind on it!" Deandré shouted back at his wife, sweat pouring from his forehead.
"This is your child, Deandré! That don't mean *nothin'* to you?" Kiasha asked, her urban voice now cracking from the overwhelming sense of betrayal she felt.
"Not when I got some crazy-ass bitch tellin' me she feel my son break-dancin' in her damn uterus!" Deandré roared back at his wife, his words like daggers into her womb.
Kiasha collapsed onto her knees with her face in her hands and began to sob. She couldn't take this any longer, she needed him to trust her that their son would become a break-dancing prodigy. If he only had the same hope for the future as she did, he would want to continue on with their marriage and take part in parenting their child.

title: A Tyler Perry-themed story that I began to write one night

question: Why is Deandre so upset that Kiasha is saying that the baby is break dancing in her womb?

answer: Unclear.

question: Write a ~2 sentence summary.

answer: Deandre is arguing with his pregnant wife Kiasha because she keeps insisting that their baby is break dancing in her womb and that it is a prodigy. Deandre, who is often abusive, is so annoyed at her absurd statements that he wants to divorce her.


text:
SEAN MATTHEW CLANCY (born October 22, 1956) is a former American football linebacker who played two seasons in the National Football League with the Miami Dolphins and St. Louis Cardinals from 1978 to 1979.

Career

Clancy was drafted by the Dolphins in the 8th round of the 1978 NFL draft out of Amherst College. Clancy would go on to appear in 26 career games for the Dolphins.[1]

[1]

title: Sean Clancy (American football)

question: Who is Sean Matthew Clancy?

answer: a former American football player

question: What position did Sean Matthew Clancy play?

answer: linebacker

question: What teams did Sean Matthew Clancy play for?

answer: the Miami Dolphins and St. Louis Cardinals

question: How many NFL games did Sean Matthew Clancy participate in?

answer: 26

question: Write a ~2 sentence summary.

answer: Sean Matthew Clancy is a former American football linebacker who played from 1978-79. He was on the Miami Dolphins and, later, the St. Louis Cardinals.


text:
KAMOKUIKI (c. 1795 – September 26, 1840) was a grandmother of the last two ruling monarchs of the Kingdom of Hawaii.

Life

Kamokuiki was born about 1795 as a daughter of the chief Kanepawale, son of Kaʻihelemoana and Kaʻopa, and his wife chiefess Uaua, daughter of Kaʻehunuiamamaliʻi and Koʻi. Her grandfather's sister was Hikuikekualono, the mother of Kahaopulani, who according to legend hid and nursed the baby Kamehameha I during his infancy when he was being hunted down by Alapainui.[1]

Kamokuiki married High Chief Kamanawa II and with him had a son, Caesar Kapaʻakea (1815–1866). She also had a daughter named Kekahili by another husband named Alapaimaloiki.[2] The House of Kalākaua descends from her son Kapaʻakea. The House of Kawānanakoa descends from her daughter Kekahili.

After converting to Christianity, Kamokuiki grew disgusted at her husband Kamanawa's many affairs. In 1840, she divorced him for the crime of adultery. Kamanawa was not allowed to remarry while she was alive. Six weeks after the divorce, Kamokuiki died in Honolulu on September 26, 1840.[3] Two days later an autopsy was performed on her body and her stomach was discovered to be “much inflamed, while everything else was in order.” Her ex-husband and his accomplice Lonoapuakau were arrested and placed in chains. They had poisoned her “‘awa” (a name for kava, a narcotic drink) with fatal doses of the fishing poisons ʻākia and ʻauhuhu. They were both tried by a jury of twelve chiefs and found guilty of her murder. They were hanged in the Honolulu Fort on October 20, 1840, the first two to be prosecuted under the criminal laws adopted in the Hawaiian constitution of 1840. Charles Wilkes of the United States Exploring Expedition was in Honolulu during the murder and subsequent trial. Calling her “Kamakinki”, Wilkes recounted how the cries of the natives mourning the death of Kamokuiki kept him awake at night, describing it as “one of the most startling and mournful sounds I ever heard which lasted all night, and disturbed the whole town of Honolulu.”

This incident left a mark on the family and would negatively affect public opinion of Kamokuiki's grandson Kalākaua during his campaign for the throne in 1874. Later opponents of Kalākaua and his sister and successor Liliʻuokalani would use the murder case as an example of their family's idolatrous tendencies.

Kamokuiki's remains are interred in the cemetery of the Kawaiahaʻo Church, in the Kapiʻolani family plot. Her husband Alapaimaloiki, Kūhiō Kalanianaʻole, the father of Queen Kapiʻolani, and other relatives of Elizabeth Kahanu Kalanianaʻole are also buried here. Today, an obelisk marks where the Kapiʻolani family plot is located.[4] Most of her royal descendants are buried at the Royal Mausoleum at Mauna ʻAla.

[1]

[2]

[3]

[4]

title: Kamokuiki

question: Summarize Kamokuiki's family members.

answer: Kamokuiki's father was the chief Kanepawale, son of Kaʻihelemoana and Kaʻopa. Her mother is  chiefess Uaua, daughter of Kaʻehunuiamamaliʻi and Koʻi. Her grandfather'ssister was the legendary Hikuikekualono. Her children were Kekahili and Caesar Kapa'akaea, and she was grandmother to the last two ruling monarchs of the Kingdom of Hawaii. Her murder left a mark on her family, and negatively affected public opinion on her grandson's run for the throne.

question: What does the text say about Kamokuiki's relationship with Kamanawa?

answer: Kamanawa was the husband of Kamokuiki. He had many affairs, which disgusted Kamanawa and caused her to divorce him for the crime of adultery. She died six weeks after the divorce due to Kamanawa poisoning her with fishing poisons. He was found guilty of her murder and hung.

question: Summarize the most interesting event in this text.

answer: In 1840, Kamokuiki died six weeks after divorcing Kamanawa for his adultery. It was discovered she was poisoned with fishing poisons in her kava. Kamanawa was arrested, found guilty of her murder, and hung along with his accomplice Lonoapuakau. Cries of Hawaiian natives were heard mourning Kamokuiku's death for an entire night. This event left a mark on Kamokuiki's family for years to come.

question: What does the text say about manslaughter?


text:
Persian Language
History and Origins of Persian (Parsi or Farsi) and Dari-Persian language
Persian is spoken today primarily in Iran, Afghanistan and Tajikistan, but was historically a more widely understood language in an area ranging from the Middle East to India. Significant populations of speakers in other Persian Gulf countries (Bahrain, Iraq, Oman, Republic of Yemen and the United Arab Emirates), as well as large communities around the World.
Total numbers of speakers is high: about 55% of Iran's population are Persian speakers; about 65% of Tajikistan's population are Tajik-Persian speakers: over 25% of the Afghanistan's population are Dari-Persian speakers; and about 1% of the population of Pakistan are Dari-Persian speakers as well.

[]

LINGUISTIC AFFILIATION
Persian is a subgroup of West Iranian languages that include the closely related Persian languages of Dari and Tajik; the less closely related languages of Luri, Bakhtiari and Kumzari; and the non-Persian dialects of Fars Province. Other more distantly related languages of this group include Kurdish, spoken in Turkey, Iraq, and Iran; and Baluchi, spoken in Afghanistan, Iran, and Pakistan. Even more distantly related are languages of the East Iranian group, which includes Pashtu, spoken in Afghanistan; Ossete, spoken in North Ossetian, South Ossetian, and Caucusus of former USSR; and Yaghnobi, spoken in Tajikistan. Other Iranian languages of note are Old Persian and Avestan (the sacred language of the Zoroastrians for which texts exist from the 6th century B.C.).
West and East Iranian comprise the Iranian group of the Indo-Iranian branch of the Indo-European family of languages. Indo-Iranian languages are spoken in a wide area stretching from portions of eastern Turkey and eastern Iraq to western India. The other main division of Indo-Iranian, in addition to Iranian, is the Indo-Aryan languages, a group comprised of many languages of the Indian subcontinent, for example, Sanskrit, Hindi/Urdu, Bengali, Gujerati, Punjabi, and Sindhi.

LINGUISTIC VARIATION
Scholars recognize three major dialect divisions of Persian: Farsi, or the Persian of Iran, Dari Persian of Afghanistan, and Tajik, a variant spoken in Tajikistan in Central Asia. We treat Tajik as a separate language, however. Farsi and Dari have further dialectal variants, some with names that coincide with provincial names. All are more or less mutually intelligible.

Dari Persian, mainly spoken in Afghanistan, until recently, deferred to the Tehran standard as its model, and although there are clear phonological and morphological contrasts, due partly to the influence of neighbouring Turkic languages, Farsi and Dari Persian remain quite similar. The dialectal variation between Farsi and Dari has been described as analogous to that between European French and Canadian French. Dari is more conservative in maintaining vowel distinctions that have been lost in Farsi.

Luri and Bakhtiari, languages in the southwest part of Iran, are most closely related Farsi, but these are difficult for a speaker of the Tehran standard to understand. While speakers of Luri regard their speech as a dialect of Persian, speakers of Farsi do not agree. Judaic Persian, written in Hebrew characters and used by Jews throughout Iran, is close to the Persian standard in its written form. However, many Iranians of Jewish descent have left the country and no longer form a significant portion of the population.

ORTHOGRAPHY
Persian in Iran and Afghanistan is written in a variety of the Arabic script called Perso-Arabic, which has some innovations to account for Persian phonological differences. This script came into use in Persia after the Islamic conquest in the seventh century. A variety of script forms: Nishki is a print type based closely on Arabic; Talik is a cultivated manuscript, with certain letters having reduced forms and others occasionally elongated in order to produce lines of equal length; and Shekesteh is also a manuscript, allowing for a greater variation of form and exhibiting extreme reduction of some letters. _See_[] PERSIAN ALPHABET

LINGUISTIC SKETCH
The richly inflected morphological system of Old Iranian has been drastically reduced in Persian. The language has no grammatical gender or articles, but person and number distinctions are maintained. Nouns are marked for specificity: there is one marker in the singular and two in the plural. Objects of transitive verbs are marked by a suffix. The morphological features of Arabic words are preserved in loans, thus Persian shows "broken" plural formations, that is, a word may have two different plural forms.

Verbs are formed using one of two basic stems, present and past; aspect is as important as tense: all verbs are marked as perfective and imperfective. The latter is marked by means of prefixation. Both perfective and imperfective verb forms appear in three tenses: present, past and inferential past. The language has an aorist (a type of past tense), and has three moods: indicative, subjunctive, counterfactual. Passive is formed with the verb 'to become', and is not allowed with specified agents. Verbs agree with the subject in person and number. Persian verbs are normally compounds consisting of a noun and a verb.

Word order in Persian is Subject-Object-Verb although modifiers follow the nouns they modify and the language has prepositions.

Persian distinguishes short and long vowels. Words are stressed on the last syllable.

ROLE IN SOCIETY
Persian, until recent centuries, was culturally and historically one of the most prominent languages of the Middle East and regions beyond. For example, it was an important language during the reign of the Moguls in Indian where knowledge of Persian was cultivated and encouraged; its use in the courts of Mogul India ended in 1837, banned by officials of the East Indian Company (British Colonialism). Persian scholars were prominent in both Turkish and Indian courts during the fifteenth to eighteenth centuries in composing dictionaries and grammatical works. A Persian Indian vernacular developed and many colonial British officers learned their Persian from Indian scribes.

Persian is the first language of about 55 percent of the population in Iran, and is the country's official language. It is the language of government, the media, and school instruction. Of the rest of Iran's population, 20 percent speak related Western Iranian languages and 25 percent speak Arabic, New Aramaic, Armenian, Georgian, Romany, and Turkic languages.

In Afghanistan, Dari Persian, along with Pashtu, are official languages of the country. The language is taught in schools and radio Afghanistan is promoting a standardized pronunciation of the literary language. The Persian spoken in Teheran serves as a model for more formal styles, but some colloquial styles are closer to Tajik. Only minor lexical differences exist between the literary forms used in Iran and Afghanistan. Although both Pashtu and Dari are official languages, Dari has a special social status in the country because of its historical prestige; it is the preferred language for communication among speakers of different linguistic backgrounds.

HISTORY
Old Persian is attested from the cuneiform inscriptions left by the Achaemenid dynasty (559 to 331 BC.) that ruled the lands known as the Realm of the Aryans (from which comes the name of the modern country Iran) up until the conquest of Alexander the Great.

Middle Persian, also known as Pahlavi, after the Parthians who ruled Persia after the collapse of Alexander's Empire, is known chiefly through its use in Persian's pre-Islamic Zoroastrian religious writings.

The origin of Modern Persian is not clear. Although greatly influenced and closely affiliated to Middle and Old Persian, there is no conclusive evidence that it is directly descended from these languages. It may instead derive from a Pahlavi dialect once spoken in northeast Iran.

Old Persian, by contrast, and its immediate descendant Middle Persian, originated in a province in southwest Iran that was once the center of the Persian Empire -Parsa or Fars-, hence the contemporary Persian name of the language: Farsi.

The Early Modern period of the language (ninth to thirteenth centuries), preserved in the literature of the Empire, is known as Classical Persian, due to the eminence and distinction of poets such as Roudaki, FERDOWSI, and KHAYYAM. During this period, Persian was adopted as the lingua franca of the eastern Islamic nations.

Extensive contact with Arabic led to a large influx of Arab vocabulary. In fact, a writer of Classical Persian had at one's disposal the entire Arabic lexicon and could use Arab terms freely either for literary effect or to display erudition.

Classical Persian remained essentially unchanged until the nineteenth century, when the dialect of Teheran rose in prominence, having been chosen as the capital of Persia by the Qajar Dynasty in 1787. This Modern Persian dialect became the basis of what is now called Contemporary Standard Persian. Although it still contains a large number of Arab terms, most borrowings have been nativized, with a much lower percentage of Arabic words in colloquial forms of the language.

The term "Persia(n)" derives from the Greek and is based on the Ancient Greek reference to the whole region. "Farsi" is the Arabic equivalent for the name of the southwestern province of Parsa the locus of various Persian dynasties. "Iran" derives from an Old Iranian word.

question: What language does this article discuss?

answer: The Persian language.

question: How is Persian written?

answer: In a variety of the Arabic script called Perso-Arabic

question: What are the three major dialect divisions of PErsian?

answer: Farsi in Iran, Dari in Afghanistan, and Tajik in Tajikistan and Central Asia.

question: How many speakers does Persian have?

answer: It is not mentioned, however it is mentioned that about 55% of Iran's population are Persian speakers, about 65% of Tajikistan's population are Tajik-Persian speakers, over 25% of the Afghanistan's population are Dari-Persian speakers, and about 1% of the population of Pakistan are Dari-Persian speakers as well.

question: Write a ~4 sentence summary.

answer: This article describes the Persian language and its dialects. It begins with some linguistic background, discussing its linguistic affiliation and dialects, such as Farsi, Dari, and Tajik. It continues with a description of Persian orthography and other linguistics features. The article concludes with a sociolinguistic description and a brief history of the language.


text:
KWADWO NKANSAH (born 15 April 1987) professionally known as Lil Win, is a Ghanaian artist, musician, actor and comedian.[1][2] Kwadwo Nkansah was born to Mr Kofi and Ama. He grew up with six other siblings in Kwaman in the Ashanti region.[3] He is the founder of Great Minds International school in Kumasi, Ashanti Region of Ghana.[4]

Town

Kwadwo Nkansah hails from Wassa Akropong, in Western Region of Ghana.

Education

Kwadwo completed Junior High school at Kenyasi Abrem in the Ashanti region but wasn’t able to further his education.[5]

Marriage

Kwadwo Nkansah married Patricia Afriye in 2012 and had two children (sons) with her. After four years the marriage broke down and led to a divorce.
==Filmography==

-   _Sex Education_
-   _Wrong Turn 3_
-   _Pleasure Or Pain_
-   _Once Upon a Time in Accra_
-   _Maye Papa Enu Me Ho_
-   _Akurase Tumi_
-   _A True Life Story_
-   _Satan_
-   _Condom Producer_
-   _Okwantu Ni Mobrowa_
-   _Onaapo_
-   _Emre Bi_
-   _Sure banker_
-   _David Ba_
-   _Suro Nipa_
-   _Aden Ne Otan Hunu_
-   _Bone Akyi Akatua_
-   _Armageddon_
-   _Ensei Me Din_
-   _Nipa Nye Nyame_
-   _Azonto Ghost_
-   '' Obra Twa Owuo''
-   '' Abusua Bone''
-   '' The Most Wanted''
-   '' Y3 Gye Ya Konya''
-   '' Sika Mpe Rough''
-   '' Amakye n Dede''
-   '' Magye Maniso''

Music Career

1.  Mama Boss Papa (Yimama) ft. Young Chorus
2.  I Dont Think Far (Languages) ft Jupitar, Edem, Tinny, Pope Skinny x Cabum
3.  Okukurodurufuo (ft Ohemaa X Dadao x Top Kay)
4.  Pidgintoi ft Mzvee
5.  I Dont Think Far ft Top Kay X Young Chorus and Spermy
6.  Twedie
7.  I Dont Think Far (Remix) Ft Guru, Flowkingstone, Sherry Boss & Zack
8.  Anointing Ft Kuami Eugene
9.  How Dare You ft Article Wan

Achievements

He won “Favorite Actor” at the sixth edition of the annual Ghana Movie Awards (GMAs)in 2015.

He was honored by the United Nations for his campaigns against the illegal immigration in West Africa.[6]

[7]References

Category:Ghanaian comedians Category:People from Kumasi Category:Ghanaian male film actors Category:1987 births Category:Living people

[1] {{ cite web|title=Read the Full Biography of Kwadwo Nkansah Lil Win|url=http://ghananewsonline.com.gh/read-full-biography-kwadwo-nkansah-lil-win/%7Cpublisher=Ghananewsonline.com.gh%7Caccessdate=10 April 2018}}

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title: Kwadwo Nkansah

question: Who is Lil Win?

answer: Lil Win is Kwadwo Nkansah.

question: Where is Kwadwo Nkansah from?

answer: He is from Ghana.

question: How is Nkansah related to Patricia Afriye?

answer: Patricia Afriye was Nkansah's wife.

question: What awards did Kwadwo Nkansah receive?

answer: He won 'Favorite Actor' at the sixth edition of the annual Ghana Movie Awards in 2015.

question: Write a ~4 sentence summary.

answer: Kwadwo Nkansah is a Ghanaian artist, musician, actor, and comedian. He is professionally known as Lil Win. He is the founder of Great Minds International school in Kumasi, Ashanti Region of Ghana. He won 'Favorite Actor' at the sixth edition of the annual Ghana Movie Awards in 2015.


text:
                                          Me

	Before we get into the depths of this story, I assume you are going to want to know about me. Who am I? Where did I come from? All that basic shit. And the truth is, who I am isn’t all the different from who the girl next door to you is. My situations have made me unique and the fact that I observe has made me different.

	At this point in time, I am 19 years old. I am slightly overweight, but you wouldn’t notice from looking at me. I have hips that one day will make giving birth easy but for now just make black guys go dammmmmnnnn girrllll. I have shoulder length hair that is some weird boxed shade of red that I dyed it out of anger. The cut was out of anger too. I’m 5’3.5 and yes that half an inch does matter. I wear a dress almost every day, not because I’m particularly girly anymore, but because it’s really all I have from my last relationship which was particularly controlling. I have two tattoos. One of an owl rests on my left ankle and the kittens from the aristocats parade around my right ribcage. Appearances make a person. This is why I am going so in depth so you can know me. My eyes, well they aren’t important. I want you too see my situations through your eyes. So take your eyes, put them on me, and there we go.

	As someone told me, my personality is weird. I took compliments when I was called quirky. Eccentric even was nice. Now I have just gone off the deep end, into plain weird. But, as you will learn, I was not always this way. I once had it together and knew how to control the weirdness. Now it just kinda spews out like some verbal garbage. It’s gross. But if people can laugh at me and their day is brightened, then awesome. I am someone what a perfectionist. Okay, complete lie there. I am a total perfectionist. I have a little motto in my head that say I must be “prim and proper and polite” at all times. I am working on this. As we all know, this is impossible. I did not know this until recently. The fact that I thought I could be perfect has led me to many a mental illness which we will get into latter. That is not important when trying to learn about the essence of me. And I think the essence of me which you need to know is that I am quirky, caring, and I can see into your soul weather you want me too our not.

	That last part is a little creepy, but that is besides the point. I will know when you want help or need help, regardless if you think you do. And that freaks most people out. I’ve had this super lame “gift” since I can remember. It’s more of a hassle than anything and leaves me stressed out. At any given moment I am flipping through my phone seeing if  I have someone’s number to see if they are ok. I can usually tell you exactly what’s wrong with them, and that’s kinda sucky too. People think this is total BS until I call them at 10pm at night and tell them that no, they should not go spend their last $20 on a little bit of weed. That they should take some advil and a bath and go to sleep and they will be just fine. Just wait till I do it to you. You will be scared. The knowing what’s up with everyone has gotten my head into a tizzy more often than once. I don’t stop to smell the roses or you know think about myself and eat sometimes, because I get so worked up about everyone else. Maybe that shows a great thing about my character. Maybe not.

	I think the most important thing that you know about me is, I did lose me for awhile. For a good chunk of 2 year I would say. I think I was brain washed. I really don’t know. But when you fall under the spell of a sociopath’s love, you do what they want. Not to say I never loved him, because I did, and still do, and probably always will, but he screwed me up. When you are 16 and 17 and 18 you should be finding who you are. Not being pushed into some mold. And if you get anything out of what I write it is that. Because here I am at 19, trying to make up for lost time and it sucks. But like everything else, we will get back to that lost time, we will get back to the sociopath I love(d). Because, while love is insignificant, it is important. Expecially when you can say it helped create the monster the in your head.

	There are other little things about me that aren’t important. Hobbies, jobs held, heck even friends. These will fall into place when they need to. Setting of my life is a small town in California. Just think of where you live, it’s much like that. A suburban town with nothing to do, no where to go. Tons of time to get trapped in your head. I want you to step into my shoes, but don’t lose who you are. We are one on this journey. And you are in for a ride.

title: The beginning of my short life story

question: In the course of the narrator's love life, how did her relationship change her or shape her into what she is now?

answer: The narrator is a 19-year-old girl who described herself as a people pleaser. When she was 16, she got into a relationship with a guy she loved very much, even until their breakup, but he was controlling. Coming out of the relationship opened her eyes and made her see life differently. Furthermore, the result of the breakup also led her to cut her hair to shoulder length and dye it red. She admits that even though love is insignificant, it's essential. Currently, she's trying to make up for the years she lost during her relationship.


text:
DEAR MEMBERS:

I am writing to share the great news that we have reached an “agreement-in-principle” to play the future home games of the Parramatta Eels at the magnificent Western Sydney Stadium. This agreement-in-principle commences in 2019 and confirms the Parramatta Eels will be a key anchor tenant at Western Sydney Stadium.

Following detailed negotiations with the stadium operator (VenuesLive), our Board and Management are satisfied that all issues have been addressed and the focus is now on ensuring Western Sydney Stadium and the Parramatta Leagues Club precinct will deliver the best game day experience for our Members, corporate partners and community stakeholders.

The Opening Game at Western Sydney Stadium is scheduled to be our home game in Round 6 of the 2019 NRL Premiership against the Wests Tigers on Easter Monday, 22 April 2019.

We are extremely pleased to have reached this stage and to confirm Western Sydney Stadium as our new home. This Stadium will provide our Members and commercial partners with an outstanding game day experience and will also contribute to the Club’s financial stability, allowing us to invest further in our Football teams.

On behalf of the Parramatta Eels Club Board and Management, I would like to thank VenuesLive for the constructive dialogue and helping us to give our Members and fans an outcome ahead of the 2019 NRL Draw being announced shortly.

Thank you all our Members for your continued support and loyalty - we can’t wait to welcome you into our new Blue & Gold fortress in 2019!

Best wishes.

BERNIE GURR
CEO
PARRAMATTA EELS

question: Who are the Eels playing on April 22?

answer: The Eels are playing the Wests Tigers on April 22.

question: Where is the Eel's new home?

answer: The Eel's new home is the Western Sydney Stadium.

question: Who is the CEO of the Parramatta Eels?

answer: Bernie Gurr is the CEO of the Parramatta Eels.

question: What round of the NRL Premiership are they about to play?

answer: They are about to play Round 6 of the NRL Premiership.

question: Write a ~2 sentence summary.

answer: The CEO of the Parramatta Eels writes to their members to announce they have a new home stadium. They say that they are excited for this move and are excited for their upcoming game.


text:
The Federal Energy Regulatory Commission (FERC) voted Thursday to implement rules that are designed to remove barriers to grid-level batteries that store electricity.

The new regulation requires that electric grid operators pay and treat storage operations similarly to how they treat power plants.

“This order will enhance competition and promote greater efficiency in the nation’s electric wholesale markets, and will help support the resilience of the bulk power system,” the commission said in a statement after its vote.

All five of the commissioners — three Republicans and two Democrats — voted in favor of the proposal.

“Not only is this rulemaking a win for both consumers and industry, but it is also the kind of positive regulatory action that removes barriers to competition, allowing emerging technologies to compete in the marketplace,” said Commissioner Neil Chatterjee[]Neil ChatterjeeOVERNIGHT ENERGY: House Democrats push Biden to pick Haaland as next Interior secretary | Trump administration proposal takes aim at bank pledges to avoid fossil fuel financing | Wasserman Schultz pitches climate plan in race to chair Appropriations Senate advances energy regulator nominees despite uncertainty of floor vote OVERNIGHT ENERGY: Trump takes major step toward Alaska wildlife refuge drilling opposed by Biden | Grijalva backs Haaland for Interior Secretary | Obama alumni considered top picks for Biden Energy secretary MORE, a Republican.

“It is something of a cliche to refer to electric storage as a game changer, but it is also true. Given the ongoing changes in our nation’s resource mix, and the changing capabilities needed to serve customers, electric storage is poised to provide a critically important role,” said Commissioner Cheryl LaFleur, a Democrat.

Storage technology has made significant strides in recent years, but still plays a relatively small role in the electricity mix. Only about 23 gigawatts of storage capacity is in operation nationwide, the vast majority of which is hydroelectric plants that can pump in reverse to store water that can later be run through the plant, according to the Energy Information Administration.

One of the primary uses for electricity storage is to take power during periods of low demand and dispatch it when demand and prices are higher.

But as intermittent energy sources like wind and solar power grow in use, storage can hold power generated when the wind or sun is strong so that it can be used later, when demand outpaces generation.

Sens. Sheldon Whitehouse[]Sheldon WhitehouseThe Hill's Morning Report - Presented by the UAE Embassy in Washington, DC - COVID-19 fears surround Thanksgiving holiday Feinstein departure from top post sets stage for Judiciary fight Whitehouse says Democratic caucus will decide future of Judiciary Committee MORE (D-R.I.) and Ed Markey[]Ed MarkeyUS national security policy in the 117th Congress and a new administration OVERNIGHT ENERGY: Biden eyes new leadership at troubled public lands agency | House progressives tout their growing numbers in the chamber at climate rally | Trump administration pushes for rollback of Arctic offshore drilling regulations House progressives tout their growing numbers in the chamber at climate rally MORE (D-Mass.) had been two of the most vocal voices calling for FERC’s storage rule.

“We’re already seeing powerful new batteries help renewable energy beat out fossil fuels. This rule will help continue that success, reducing carbon pollution and providing Americans with dependable, low-cost energy,” Whitehouse said in a statement.

The storage industry praised FERC's action.

“With this morning’s unequivocal action, the FERC signaled both a recognition of the value provided by storage today, and more importantly, a clear vision of the role electric storage can play, given a clear pathway to wholesale market participation,” said Kelly Speakes-Backman, CEO of the Energy Storage Association.

question: What type of batteries/what sizes are we talking about?

answer: Unclear, but implied to be very large so as to compare to a power plant.

question: What's a use case for these grid-level batteries?

answer: Storing excess energy created during times of low demand for use during times of high demand.

question: When was this article written?

answer: Sometime between the Trump and Biden administrations.

question: How do dams qualify as energy storage?

answer: They consider the energy potential of stored water to be energy storage.

question: Write a ~3 sentence summary.

answer: The Federal Energy Regulatory Commission voted to implement rules that remove barriers to grid-level batteries to store electricity. Electric storage is considered a game changer with potential to greatly reduce costs and offer augmented supply capacity. They will help reduce carbon pollution and provide Americans with dependable, low-cost energy.


text: Darth Vader smoked cigarettes. Up there in space without anyone to talk to, he had nothing but time. The life he never lived floated by the 4-foot thick window bleeding out of focus with the smoke that twisted around until it hung in a solid mass that floated away too. Wouldn’t it be nice to have more than galactic domination? Not the universe per say, but perhaps that family he’d mistakenly "killed". He had never truly met his son. Did he even know that his father was Darth Vader, would he ever believe such a fact? And that’s why the cigarettes plugged the burning flare of holes in his clouded suit of woe. No, everything happens one way and couldn’t possible happen any other. For the pain of his everyday life, he did exceptionally well. He was slow now, but it wasn’t because of smoking. Everyday when he would return to his hibernation chamber, the droids would clean his armor and lungs. But not like that matter, the air filter on his mask almost let in nothing but clean air. So why cigarettes he’d ask himself? Because it was space and it was his fucking choice. It was his legacy, to look stupid by himself to himself with a cigarette when he wasn’t throttling rebels. Fuckit. Maybe he should learn an instrument. The organ would be ideal. As the Captain of the ship and second in command of the Empire, that seemed about right. But until then, he could only wish and pretend. Nobody knew what he was thinking when he was not in battle or a cut scene.  That was nice and kept him extremely intimidating.  No one but his droids had ever seen his scrap book or his cigarettes. Surely that would cause some unease as to his true power. Though it would be eternally unmatched, the fact that he had a journals full of pictures of cats and cute animals might do some unintended damage if let into the wrong hands. But he was not worried; everyone was terrified of him already. Underneath it all, he was as human as anyone. He was just simply doing his job; fear and intimidation of the entire universe. But every now and then, the guilty pleasures would leak through like a joyful memory of his childhood watching the two suns set, or his adolescence with the Queen. Their nights out on the plains of Naboo. How different things could be. Had he listen or not listened to Palpatine was unimportant now. Things ran their course the way they were supposed to. He thought of how ridiculous everyone would have considered George Lucas if Darth Sidious and himself were friendly. The legacy of his would not be as immortal. But enough with deep thought, it was almost time to invade Kashyyyk with the 501st. He must redirect his thoughts to the importance of this upcoming victory they had planned. Maybe this battle would yield something more than bloodshed…he had a strange feeling it somehow would.

title: Darth Vader Smoked Cigarettes

question: Who smokes cigarettes?

answer: Darth Vader

question: What does he maintain was a mistake?

answer: That he killed his family.

question: Who are the only entities to ever have seen his scrap book or his cigarettes?

answer: His droids.

question: Why does he smoke?

answer: Because it is his fucking choice.

question: Write a ~4 sentence summary.

answer: Darth Vader takes up a cigarette habit and ruminates on how crummy his life has been. He enjoys the freedom of choice. Only his droids, who clean his lungs and armor in the chamber each night, are privy to this habit of his. He has a feeling his next battle will yield something other than bloodshed.


text:
The CHURCH OF SÃO JOSÉ () is a 17th-century church located in the civil parish of Fajã Grande in the municipality of Lajes das Flores, in the Portuguese island of Flores, in the archipelago of the Azores.

History

In July 1676, the ecclesiastical parish of Nossa Senhora do Remédios de Fajãzinha was instituted, that included several localities: Fajã Grande, Ponta, Caldeira and Mosteiro, by proviso of the Bishop of Angra, friar D. Lourenço de Castro.[1]

In 1755, a chapel dedicated to São Jorge was constructed, that would eventually be the site of the actual church.[2] The chapel was consecrated on 24 May 1757 and its burial occurred in January 1758.[3]

In 1847, the chapel was expanded and concluded in 1849, with its consecration occurring on 1 August 1850.[4]

On 28 November 1855, the _Junta Geral do Distrito da Horta_ (_District General Junta for Horta_) complained to the government about the creation of the autonomous parish of Fajã Grande.[5] A report by the Civil Governor Luís Teixeira de Sampaio (dated 3 April 1857), affirmed that the chapel of São Jorge was large enough to be constituted as its own parish; owing to its size and distance (a _league_) from Fajãzinha and separated by a _running ravine, that in the winter cuts off completely the communication [between settlements]..._, that it would be _a great service to those people_ that a separate faith community be established.[6] Legend suggests that, on those days when the Ribeira Grande ravine overflowed its banks, impeding passage to Fajãzinha, the local parishioners congregated at what became known as the _Pedra da Missa_ (_Mass Stone_).[7] Located on the right bank of the ravine, the parishioners would face the church of Fajãzinha, which they could see, praying during the liturgical mass, and dispersing when the locals ended their service. On 2 December, the General Junta (once again) protested to the central government that the settlement should not be de-annexed.[8] But, on 4 April 1861, King D. Pedro V authorized the creation of the new parish, to be constituted by the localities of Ponta, Fajã Grande and Cuada, with its seat in the church of _São José da Fajã Grande_.[9] On 20 June, a charter was issued by Bishop of Angra, friar Estêvão de Jesus Maria elevated the parish, separate it from the established _Nossa Senhora do Remédios de Fajãzinha_.[10]

In 1880 there were public works associated with the interventions by a Fajãgrandense emigre, José Luís da Silveira, who had moved to the United States.[11]

Architecture

The triumphal arch is flanked by two collateral retables.

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title: Church of São José (Fajã Grande)

question: Where is the Church of Sao Jose located?

answer: It is located in the civil parish of Faja Grande in the municipality of Lajes das Flores, in the Portuguese island of Flores, in the archipelago of the Azores.

question: When was the chapel dedicated to Sao Jorge consecrated?

answer: It was consecrated on May 24, 1757.

question: Who stated that the chapel of Sao Jorge was large enough to be constituted as its own parish?

answer: A report by the Civil Governor Luis Teixeria de Sampaio affirmed that the chapel of Sao Jorge was large enough to be constituted as its own parish.

question: How can you describe the architecture of the church?

answer: The church has a triumphal arch which is flanked by two collateral retables.

question: Write a ~1 sentence summary.

answer: This article describes the construction of the church of Sao Jose in great detail.