The Agency Bias in Creativity Evaluations: The Role of Implicit Beliefs about Creativity
Bibliographic record
Abstract
Although past research has suggested that older workers are stereotyped as less creative, little is known about mechanisms that underlie this belief and the conditions under which this bias is likely to occur. Past research suggests that people construe creative individuals as highly agentic individuals who can produce radically different creative ideas. We suggest that these implicit beliefs about creativity would disadvantage creative evaluations of older workers as they are often perceived lacking in agency. Four studies, including experimental and archival data from Fortune 500 employees and M.B.A students, support our predictions. Study 1 analyzed archival data from M.B.A. students, finding that older targets were perceived as less innovative. Utilizing archival data from Fortune 500 employees, Study 2 found that older workers are evaluated as less creative; but this age bias in creativity evaluations occurred only when perceivers associate creativity with radical creativity. Study 3’s experiment found that an older target was perceived as less creative, even when described as producing identical output as a comparable younger target. Finally, Study 4’s experiment found that older targets were evaluated as less able to develop radically creative ideas because they were perceived as lacking in independent, diligent, and competent agency.
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 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 | 0.007 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".