Learning to Read the Bible with Desire: Teaching the Eros of Exegesis in the Theological Classroom
Bibliographic record
Abstract
Abstract. The article begins with two brief theoretical descriptions of a pedagogy of desire vis‐à‐vis the Christian Bible. The first of these is a poem; the second summarizes the conversation constituted by four quite different books: the Confessions by Augustine of Hippo, Freud & Philosophy by Paul Ricoeur, Pedagogy of the Oppressed by Paulo Freire, and The Ethnography of Reading edited by Jonathan Boyarin. There follows, then, a case in point: an account of my most recent effort to teach the eros of exegesis at Emmanuel College (Toronto), using the Song of Songs. This account includes discussion of the (pre)conception(s) of the (biblical) text that inform(s) this undertaking and of the practice of communal reading as a specific type of bodily activity and social experience. In conclusion, the question of evaluation is addressed. How does one learn to love – when, by, in, with, and under – reading the Bible?
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.004 |
| 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".