Co-Authorship Trends in Philosophy of Education Journals in the US and Canada
Bibliographic record
Abstract
A variety of epistemic practices and norms influence how knowledge and understanding are advanced in academia. Co-authorship practices and norms, the focus of this paper, have implications for the epistemic resources that are brought into individual scholarly works and how the resources are distributed among networks over time. Although co-authorship is widely accepted in social scientific research in education, single authorship has remained predominant in philosophy of education. This paper is part of a project exploring co-authorship practices and norms in philosophy and, in particular, philosophy of education. We aim to develop an empirical understanding of co-authorship trends in four primary philosophy of education journals in the United States and Canada. We examine the frequency of co-authorship in these outlets over the last two decades, the participants in co-authored projects, and the philosophical topics that are being explored through co-authorship. Our findings indicate that these venues are publishing co-authored works with increasing frequency and that most co-authorship is happening among faculty collaborators and among scholars who share common disciplinary backgrounds. The observed increase in the practice of co-authorship in these philosophy of education journals points to the significance of exploring it in greater depth, including giving attention to questions of ethics and epistemology that co-authorship raises, as well as to comparative analyses of trends around the world.
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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 | 0.010 | 0.079 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.031 | 0.056 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".