Bibliographic record
Abstract
This paper estimates the heterogeneity in peer effects among research scientists in terms of network position. I propose a new measure, brokerage degree, that determines the extent to which a scientist depends on a coauthor to provide him unique access to other scientists further away. I apply this measure to the coauthorship network of medical scientists. I show that network position is crucial for productivity by facilitating access to nonredundant knowledge. Identification results from variation in brokerage degree among coauthors linked to a star scientist who dies. A one standard deviation increase in the brokerage degree of a deceased star is associated with a 10% decrease in annual publications of his coauthor. By applying brokerage degree to topics, I provide evidence that access to knowledge flows embodied in scientists further away can account for a large proportion of the identified heterogeneity effect. This paper was accepted by Toby Stuart, entrepreneurship and innovation.
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.
How this classification was reachedexpand
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 | 0.035 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.028 | 0.214 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".