Bibliographic record
Abstract
While most “World Religions” curricula are employed in a wider view to liberal arts education, rather as specifically theological or religious-centered, there are several approaches which can be made to form a more constructive learning working with the existing “textbooks” circulating (treated here in English) in a kind of metaphysical way in diverse cultures whose needs are more concrete. This paper addresses two key ways in which the popular “World religions” curriculum can be, to paraphrase Tomoko Masuzawa, “re-invented” as an integral aspect of learner-based pedagogy. First, by taking the disembodied “text” and analyzing its role, content, and purpose as a learning object by situating it in the world of internet, online education, the context of learning will be seen to require what might be called energetic “points of reception”. Those points of reception can, in this second case, be seen as an individual and contextual reworking of the “world religions”, not by denying the content of the textbooks, but by subjecting its view to the actual societies, schools, and nations which employ them. While much scholarship has recently examined “religion”, “world religions”, and their definitions, this paper works on two broad themes (reception and contextualizing knowledge) to imagine avenues of engaging with what Canadian philosopher Charles Taylor calls “social imaginaries” in which students discern their own sociological, philosophical, and political imaginations on global and local religious cultures.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.044 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".