Threshold concepts in religious studies: A qualitative and theoretical exploration of threshold concepts in a “nodal” curriculum
Bibliographic record
Abstract
Abstract This article explores “threshold concepts” in North American religious studies undergraduate education. The threshold concepts approach concentrates on how certain concepts or learning experiences can act like the threshold of a doorway that opens onto a new perspective for the learner. Crucially, they come into play in learning to think like a professional within a discipline. Little work has been done on threshold concepts in religious studies. In this article I explore what threshold concepts might be central to it. I also distinguish religious studies as a “nodal” discipline, in contrast to “sequential” ones, and describe how threshold concepts function in a nodal curriculum differently than they do in a sequential one. Drawing on the Scholarship of Teaching and Learning literature, plus my own focus group data from religious studies faculty and students, I argue that the threshold concepts approach is useful for religious studies professors examining what concepts should be at the heart of our curricula and what it means to “think like a religious studies scholar.”
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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 | 0.021 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.028 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.005 |
| 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".