Examining the Evolution of the Field of Public Administration through a Bibliometric Analysis of <i>Public Administration Review</i>
Bibliographic record
Abstract
Abstract In 2015, Public Administration Review celebrated its 75th year of publication. For this milestone, the PAR Editorial Board selected the 75 most influential articles in the history of the journal and invited scholars to “revisit a selection of these articles” in order “to take stock of what these articles meant for the field.” Bibliometrics offers a complementary view of the history of a discipline and the evolution of its research and practice agendas through an analysis of its published literature. This article examines the changes over time in PAR from 1940 through 2013 in authorship: contributions, impact, gender composition, institutional and national affiliation, profession as scholar or practitioner, collaboration networks, and the status of the 75 influential articles. Through an extensive quantitative analysis of scholarly production, this article demonstrates PAR’s centrality to the discipline of public administration and its bridging role between public administration and political science.
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 | 0.021 | 0.106 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.067 | 0.106 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".