Should you bank on your network? Relational and positional embeddedness in the making of financial capital
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
This study explores the mechanisms through which relational embeddedness affects the performance of banks in syndication networks formed in the Canadian investment banking industry. I argue that banks have a choice between building embedded network ties that are overlaid with social context and arm’s-length ties that facilitate individual competition. Contrary to the arguments advanced in previous studies, I propose that maintaining a mix of arm’s-length and embedded relationships represents a disadvantageous network strategy. Such strategy not only simultaneously exposes investment banks to competition from their peers, relying primarily upon embedded or arm’s-length ties, but also sends confusing signals about banks’ networking behavior. I also propose that the link between relational embeddedness and performance is moderated by banks’ positional embeddedness, reflected in their status, and find that banks of higher status extract greater benefits from maintaining embedded ties, as compared with banks of lower status.
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 | 0.000 | 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 | 0.000 | 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) | 0.000 | 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