Judging Older Targets' Discourse: How Do Age Stereotypes Influence Evaluations?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Young adults viewed then read either good or poor descriptions of a cartoon under the guise that the descriptions were produced by young (aged 21 years), young-old (aged 65 years), or old-old persons (aged 81 years). On a rating of quality, description type interacted with target age. For young targets, good descriptions were judged as good (assimilation to expectation) and poor were rated as very poor (a contrast effect). For young-old targets, for whom expectations were lower than for young targets but not as low as for old-old targets, good performance was perceived as very good and poor performance very poor (contrast effects). For old-old targets for whom negative age stereotyping would lead to lowest expectations for performance, poor was rated as poor (assimilation to expectation) but good performance was rated as very good (a contrast effect). Young raters use a shifting standard to judge the performance of older people.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it