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Record W4206700969 · doi:10.1163/22124810-2020004

Deliberating across Difference

2020· article· en· W4206700969 on OpenAlexaboutno aff
Afsoun Afsahi

Bibliographic record

VenueJournal of Law Religion and State · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Society, and Development
Canadian institutionsnot available
Fundersnot available
KeywordsDeliberationArbitrationPerspective (graphical)EmpathyPolitical scienceScale (ratio)Key (lock)Deliberative democracySociologyLaw and economicsPublic relationsLawSocial psychologyPsychologyComputer scienceDemocracyGeographyComputer security

Abstract

fetched live from OpenAlex

This paper examines two cases of deliberation on the issue of religious arbitration in Canada: first, the Sharia law debate in Ontario (deliberation in the larger public sphere); and second, a deliberation on religious arbitration in British Columbia (deliberation in a small-scale structured setting). Relying on both secondary and original data, this article demonstrates that while the Sharia law debate failed to fulfill the key functions of a deliberative engagement, the small-scale deliberation was able to achieve all three functions: participants had the chance to express their opinions; there was ample dialogue and communication evident by increased empathy, perspective-taking ability, and knowledge gains; and finally, participants were able to come to a decision, however broad, together. Through this comparison, the article highlights key barriers to deliberation across differences and concludes with some suggestions for carrying out such engagements in the future.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.052
metaresearch head score (Gemma)0.097
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score0.277

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0520.097
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0170.035
Scholarly communication0.0120.012
Open science0.0030.029
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.036
GPT teacher head0.330
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2020
Admission routes1
Has abstractyes

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