Do Birds of a Feather Always Flock Together? Deep-Level Diversity as an Organizing Social Principle for Task-Relevant Relationships
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
Abstract Homophily—or, the preference for similar others—has been well documented through empirical evidence. However, upon further investigation, certain applications of homophily in the workplace may give some pause for thought. For instance, more research is needed to examine the boundary conditions of homophily within work teams, such as individual characteristics and contextual factors. Accordingly, the current study reexamined the finding that homophily predicts human relationships, by looking at the relation between deep-level diversity and (a) social relationships, (b) task-relevant relationships, and (c) team performance. Results from a laboratory study with 139 teams (417 participants) indicated that (1) deep-level diversity drives positive, task-relevant relationships, (2) deep-level similarity drives negative, task-relevant relationships, and (3) deep-level diversity marginally predicts team task performance. Theoretical and practical implications are discussed.
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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 | 0.001 | 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 | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it