Assessing the Elite Publication Benefits of Academic Pedigree: A Joint Examination of PhD Institution and Employment Institution
Bibliographic record
Abstract
This descriptive study is a joint analysis that assesses the relative importance of PhD institution vs. employment institution for publication success in elite accounting journals. Specifically, we examine the association between academic pedigree (i.e., graduating from and/or being employed at a top 25, 26–50, or 51–75 accounting program) and publication success in elite accounting journals from 1990 to 2013. Our pairwise and multivariate analyses quantify the significant associations between (1) published articles and whether faculty graduated from top 25, 26–50, or 51–75 accounting programs, (2) published articles and whether faculty were employed at top 25, 26–50, or 51–75 accounting programs, and (3) published articles and whether faculty jointly graduated from and were employed at top 25, 26–50, or 51–75 accounting programs. We also find differences for top 3 vs. top 6 accounting journals, and for private vs. public institutions. Overall, the analyses reveal that employment institution is more significantly associated with publications in elite accounting journals than the PhD institution, while the PhD institution is generally significant only for graduates of top 25 institutions. These findings are relevant to prospective and current PhD students, faculty at elite institutions who change schools, and accounting program administrators and deans.
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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 | 0.001 | 0.001 |
| 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 | 0.005 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".