DOES RAIDING EXPLAIN THE NEGATIVE RETURNS TO FACULTY SENIORITY?
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
We track faculty for 30 yr at five PhD‐granting departments of economics. Two‐thirds of faculty who take alternative employment move downward; less than one‐quarter moves upward. We find a substantial penalty for seniority, even after richly controlling for faculty productivity, and the penalty is little changed when we allow wages and returns to seniority to differ by mobility status. Faculty who end up moving to better or comparable positions were penalized as severely for seniority while they were in our sample as faculty who stay. These results are incompatible with the raiding hypothesis. Faculty from top 10 programs are also punished for seniority but to a lesser degree than other faculty, which could reflect reduced monopsony power against such faculty if they are more marketable. All results persist when we control for prospective publications and allow lower returns for older publications. Match‐quality bias has dissipated in the post‐internet period, which may be the consequence of greater availability of information. ( JEL J62, J44, J42)
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it