8 Contextual Bible Study: An Effective Practice to Promote Inclusivity in Rural Communities and Faith Groups
Bibliographic record
Abstract
RURAL CHRISTIANS have often been stereotyped and stigmatized as intolerant.Reimer (this volume) does much to systematically address, and in many ways falsify, this stereotype, at least with respect to "evangelical" Christians in Canada.However, it is undeniably true that some Christians, rural and urban, Protestant and Catholic, have interpreted Christian scriptures (the Bible of the Old and New Testament) in ways that support, if not actually promote, intolerance.It does not have to be this way.Indeed, rural churches of all denominations possess the potential to play incredibly important roles in transforming the attitudes of congregations across Canada on issues related to cultural and religious inclusion.It is clear that religious adherence and attendance has seen an overall decline across Canada, including rural Canada.However, church service attendance levels do generally remain higher outside of major urban centres (Clark 2003, 4).For many rural communities across the country, the church or churches remain key institutional pillars.Given the foundational role churches often play in rural communities, it is necessary to acknowledge the spiritual underpinnings of such communities and recognize that they present an important avenue for action and change as we strive for deep equality across rural Canada (Banack and Pohler, introduction to this volume).
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".