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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".