“Who is my Neighbour? Interfaith Dialogue and Theological Formation” (Responses)
Bibliographic record
Abstract
The following are three response papers that were presented at the “Who is My Neighbour? Interfaith Dialogue and Theological Formation Conference,” held on October 19, 2022, and are indirectly responding to Ingrid Mattson's discussion of interfaith engagement and the public square. The first response paper by Cory Andrew Labrecque, entitled "Theological Bioethics and Interfaith-Interdisciplinary Dialogue," uses Mattson's discussion of the challenges and rewards of principled interfaith engagement in the public square as a starting place for his own reflections on the challenges and rewards of interfaith-interdiscplinary dialogue in healthcare. While interdisciplinary discussions around healthcare often take place in secular terms – and indeed, we are often told that this is the way things ought to be – Labrecque offers a powerful account, not only of what is lost when we allow the theological perspective to become muted in such discussions, but also of what can be gained when we insist upon including it. The second response paper by Lisa J. Grushcow, entitled "Interfaith Dialogue and the Public Square: One Rabbi's Response," returns directly to the notion of the public square, using the memory and words of Rabbi Abraham Joshua Heschel to do so. While Rabbi Heschel "affirm[ed] the princple of separation of church and state," he "reject[ed] the separation of religion and the human situation," a sentiment Rabbi Grushcow shares and uses as a starting point for her own critical reflections on what interfaith dialogue and engagement wants to build, and how it can be done together.
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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 | 0.012 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.014 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.015 | 0.022 |
| Insufficient payload (model declined to judge) | 0.027 | 0.008 |
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".