Problems of Citation in the Study of Religion: Who Do We Cite and Why?
Bibliographic record
Abstract
This special issue introduction contributes to emerging discussions on citation in studies of religion. What particular issues of citation arise in cultural, historical, and textual research on religious traditions? What can the study of religion contribute to the study of citation? Weaving together references to the four articles of the special issue, we identify four citational themes that are particularly relevant to the study of religion: the continuing reverberations of colonization; relations to and in canonical traditions; the conjunction of morality and economy in neoliberal academic contexts; and the knowledge that comes from naming and interacting with a wider range of sources, such as ancestors. Finally, in the conclusion we argue for a relational ethics of citation in the study of religion.
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 | 0.050 | 0.242 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.030 | 0.040 |
| Science and technology studies | 0.012 | 0.016 |
| Scholarly communication | 0.034 | 0.021 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".