Young Adult Evaluation of Men and Women Candidates in 8 Countries
Bibliographic record
Abstract
· The Young Adult Evaluation of Men and Women Candidates Database provides data collected from parallel experiments conducted in 8 countries (10 cases) from 2014 to 2018, using a 2x2x2 factorial experiment with Candidate Gender, Party Platform, and Party Label as the 3 factors. Treatments are speeches by a candidate (approximately 600 words, and including a brief candidate bio to reinforce the sex of the candidate) with the speech presenting partisan stances on 6 policy topics. Each participant was given the speech of 1 candidate (either a man or a woman candidate, from either the governing or main opposition party of the country, with the party name either stated or not listed on the speech). In total the experiments had 6,855 participants, ranging from 253 in Alberta, Canada to 1000 participants in the Texas, US experiment. The experiment was conducted on paper in classrooms in high schools, technical schools, and universities by a team of trained RAs. The study was approved by the Institutional Review Board of Texas A&M University - IRB2014-0327D.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.008 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".