Competition and Pay Inequality Within and Between Firms
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
How does market competition affect pay inequality between and within firms? Using division managers as a pool of similar workers and the Canada–U.S. Free Trade Agreement, we find that greater competition increases overall pay inequality between, but not within, firms. This null effect within firms is not driven by a lack of statistical power. Instead, we find that it arises primarily within subsamples of firms with higher predicted levels of social comparison. Increased competition leads to greater pay-performance sensitivity among the higher-paid managers within firms, while it leads to greater overpayment among the other managers. These patterns are consistent with firm principals offering higher-powered incentives to their best managers and overpaying the rest. Altogether, this study suggests that, while competition leads to greater pay inequality overall, principals aim to maintain equality within firms and do so through the differential provision of incentives among employees. This paper was accepted by Bruno Cassiman, business strategy.
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 | 0.001 | 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 | 0.000 | 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