Citations or Journal Quality: Which is Rewarded More in the Academic Labor Market?
Bibliographic record
Abstract
Research quality can be evaluated using citations or from the prestige of the journal that publishes the research. Recent studies advocate for more weight on citations, which measure actual impact, while the journal where an article publishes is merely a predictor of whether it was thought likely to have an impact. Yet there is little comprehensive evidence on the role of citations versus journal quality in evaluating research. In this paper we use data on tenured economists in the University of California system to relate their salary to their lifetime publications of 5500 articles in almost 700 different academic journals and to the 140, 000 citations to these articles. The results show little role for citations in affecting faculty salary, with an impact only one-seventh that of a measure of journal publications. The distribution of citations, whether using an h-index or the generalized h-index proposed by Ellison (2013), is also not a significant predictor of salary.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.077 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".