The ripple effect of personality on social structure: Self-monitoring origins of network brokerage.
Bibliographic record
Abstract
Despite growing interest in social network brokerage, its psychological antecedents have been neglected. One possibility is that brokerage relates to self-monitoring personality orientation. High self-monitors, relative to low self-monitors, in adapting their self-presentations to the demands of different groups, may occupy positions as brokers between disconnected social worlds. For 162 Korean expatriate entrepreneurs in a Canadian urban area, the results showed that those high in self-monitoring tended to occupy direct brokerage roles within the Korean community--in terms of their direct acquaintances being unconnected with each other. Those high in self-monitoring also tended to occupy indirect brokerage roles--in terms of the acquaintances of their acquaintances being unconnected with each other. Finally, for recent arrivals, those high in self-monitoring tended to establish ties to a wider range of important non-Korean position holders outside the community. These results (which controlled for strongly significant effects of network size on individuals' brokerage within the community) suggest a ripple effect of self-monitoring on social structure and contribute to a clearer understanding of how personality relates to brokerage at different levels.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".