Bibliographic record
Abstract
A Review of: Budd, J. (2017). Faculty publications and citations: a longitudinal examination. College & Research Libraries, 78(1), 80–89. https://doi.org/10.5860/crl.78.1.80 Abstract Objective – To study the publishing output and citation activity of faculty at research universities. Design – Bibliometric and citation analysis. Setting – Academic citation databases. Subjects – Institutions in the United States that are members of the Association of Research Libraries (ARL). Methods – This study builds on three previous studies conducted by the author looking at faculty publication productivity, which were conducted for three different time periods beginning in 1991. For the present study, the author searched Scopus by institution to collect the total number of publications and citations for the faculty of more than 100 Association of Research Libraries (ARL) member universities, covering the years 2011 to 2013. The author acquired the total number of faculty at each institution from the ARL website. The faculty number from the ARL website and publication and citation data from Scopus were used to calculate the per capita publication and citation numbers for each institution. The author calculated the total mean number of publications and the mean number of per capita publications per university. Chi tests were used to compare the means for statistical significance. Main Results – The number of both total and per capita publications for each institution went up over the course of all three studies. The mean number of total publications per university for 1991 to 1993, the first time period studied, was 4,595.8; for the time period of the current study, 2011 to 2013, the mean was 9,662.0. For per capita publications, the mean for 1991 to 1993 was 3.56 and the mean for the present study was 5.96. Based on chi-square tests, the results were found to be statistically significant. Conclusions – The study found that the number of total publications increased significantly over time, exceeding the author’s statistical expectations based on previous work.
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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 | 0.014 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.023 | 0.058 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.022 | 0.015 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.060 | 0.022 |
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".