The emergence of politics as a taught discipline at universities in the United Kingdom
Bibliographic record
Abstract
While existing disciplinary histories of political science focus on areas such as the development of research agendas, establishment of chairs and the founding of subject associations, little work has been undertaken on the history of teaching and learning. Based on extensive archival work and use of contemporaneous documents and surveys, it combines data sources, which have not previously been used in writing the history of political science. These are used to construct a history of the taught discipline which traces the development of courses and curricula within UK universities during the 20th century. In doing so, it makes a significant contribution to the history of political science, challenging existing accounts and chronologies of the development of politics in UK universities, through a more comprehensive account of its diverse origins.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →2 of 3 models called this metaresearch. This work is contested: it sits on the field's empirical boundary, and whether it counts depends on which model you asked. It is one of the 51 works in the disagreement dossier.
Archival history of how political science became a taught discipline in UK universities, tracing chairs, subject associations and curricula; the object is an academic discipline's formation.
It reconstructs the history of political-science teaching and curricula, not research practice.
Historical study of politics as a taught university discipline; adjacent history of the academic field.
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".