Doing Theology by Listening to Marginalized Voices? Methodological Elements from Encountering Indigenous Families in a Northern Canadian Community
Bibliographic record
Abstract
Based on the experience of encountering Indigenous families in a northern Canadian community, this article draws methodological elements for doing theology by listening to people who suffer marginalization. Firstly, I situate listening to marginalized voices as an act of receiving Vatican II and a way of putting into practice Pope Francis’s call for a church that goes out to be evangelized on a path of encounter and dialogue. Secondly, I question the terminology used in referring to those who are marginalized and revisit the centre-periphery paradigm from a theological perspective, in favour of the disruptive movement of bringing the peripheries to the centre, in resonance with Matthew 25. Finally, I draw lessons from the experience of listening to Indigenous families in the Canadian north, on the journey towards a theology that listens to the voice of God in those who are marginalized.
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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 | 0.023 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.069 | 0.065 |
| Scholarly communication | 0.020 | 0.006 |
| Open science | 0.007 | 0.015 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".