A Meta-Analysis of Positive and Negative Age Stereotype Priming Effects on Behavior Among Older Adults
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
OBJECTIVE: Evidence has shown that age stereotypes influence several behavioral outcomes in later life via stereotype valence-outcome assimilation; however, a direct comparison of positive versus negative age stereotyping effects has not yet been made. METHODS: PsycINFO and Pubmed were used to generate a list of articles (n = 137), of which seven were applicable. From these articles, means, standard errors (SEs), and other relevant data were extracted for 52 dependent measures: 27 involved negative age primes and 25 involved positive age primes. Independent samples analysis of variance tests were used to explore the influence of prime valence and awareness on behavior compared with a neutral referent. RESULTS: A significant main effect for prime valence was found such that negative age priming elicited a greater effect on behavior than did positive age priming (F(1,48) = 4.32, p = .04). In fact, the effects from negative age priming were almost three times larger than those of positive priming when compared with a neutral baseline. This effect was not influenced by prime awareness, discipline of study, study design, or research group. DISCUSSION: Findings show that negative age stereotyping has a much stronger influence on important behavioral outcomes among older adults than does positive age stereotyping.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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