Dancing with Strangers: Aspiration Performance and the Search for Underwriting Syndicate Partners
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we introduce performance feedback models to specify conditions under which organizations' decision makers are more (or less) likely to accept the risk and uncertainty of nonlocal interorganizational partnership ties rather than prefer embedded ties with partners with which they have either past direct or third-party ties. Learning theory suggests that organizations performing far from historical and social aspirations may be more willing to accept the uncertainty and risk of such nonlocal ties with relative strangers. An analysis of Canadian investment banks' underwriting syndicate ties from 1952 to 1990 supports predictions from learning theory and, in addition, indicates that inconsistent performance feedback (i.e., performance above either historical or social aspirations but below the other) triggers the greatest risk taking in selecting partners.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| 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