Why Gaps Matter—A Negative Hermeneutical Approach to the Reconciliation Process in the Diocese of British Columbia Based on the Example of Bishop Logan's “Sacred Journey”
Bibliographic record
Abstract
ABSTRACT This essay delves into the utilization of a negative hermeneutical approach, focusing on gaps, tensions, and the absence of elements, to enrich our comprehension of reconciliation efforts. It posits that this method aids in discerning more and less appropriate approaches to reconciliation processes. Negative hermeneutics serves as both a technique and an ongoing journey of exploration, self‐assessment, and understanding our connection with otherness. By critically engaging with perspectives, it prompts deeper questions and fosters a heightened awareness of the limitations inherent in one's viewpoint. Drawing from examples within the ongoing “Reconciliation and Beyond” initiative of the diocese of British Columbia, specifically Bishop Logan's “Sacred Journey,” the essay illustrates how this approach holds potential. It demonstrates how a focus on negative aspects—those initially resistant to conventional academic scrutiny, like silence and materiality—offers valuable insights into critical practices and academic implications. Furthermore, the essay analyses how a hermeneutical process involving receiving, deconstructing, and recreating can introduce innovative perspectives for understanding reconciliation efforts.
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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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.042 | 0.071 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".