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
Faced with confusing and sometimes contradictory research results linking team composition to performance, recent research on top management teams (TMTs) has begun to investigate hitherto unexplored variables that might influence the hypothesized relationships. Increasing attention is being paid to the nature and quality of TMT strategic decision-making processes, with scholars arguing that diversity per se will not affect performance outcomes unless that diversity is allowed to make itself felt through systematic debate. The findings presented here suggest that diversity and debate may not be enough; a powerful CEO's emotional reactions, rooted in character, may short-circuit the presumed linkages between diversity, decision-making processes, and performance. This has important theoretical and methodological implications for this research stream, helping to explain why existing large-sample research in this area has failed to produce consistent and robust results. Suggestions are made for ways to improve theorizing and research design in this important research domain.
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 | 0.002 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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