Interreligious Studies: Dispatches from an Emerging Field, edited by Hans Gustafson
Bibliographic record
Abstract
While the field of Interreligious Studies (IRS) has been "a discernable thing" for at least the past ten years, debates on "how to define, name, and bind the outer limits of this field (or subfield) [and] on what belongs in it (and what does not)," remain active. 1 The edited volume Interreligious Studies: Dispatches from An Emerging Field (hereafter Dispatches), contributes to a growing body of literature which seeks to delve into these issues, offering a diversity of takes -thirty six to be exact -on important questions such as: What is being researched in this field, and by whom?What are its historical precedents, and how does current scholarship imagine it relating to religious studies, theology, and interfaith activism?What are its theoretical, methodological, and normative orientations?What are its limits, challenges, and possibilities?While these and other questions are explored over the volume's five different sections, editor Hans Gustafson uses the preface and introduction to contextualize the volume in relation to pre-existing scholarship, clarify its organizational structure, and offer some important notes on terminology.In terms of contextualization, Gustafson notes that while previous publications in this vein have tended to thematically skew towards a focus on interreligious pedagogies and curricular development, 2 Dispatches was curated to focus "primarily on research and scholarship" (xiv).In terms of 1.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".