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Record W4211256297 · doi:10.1111/jols.12349

Child welfare, Indigenous parents, and judicial mediation

2022· article· en· W4211256297 on OpenAlexaffabout
Robert Leckey

Bibliographic record

VenueJournal of Law and Society · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsMcGill University
Fundersnot available
KeywordsIndigenousMediationEconomic JusticeWelfarePolitical scienceAccommodationTransformative mediationState (computer science)LawSociologyAlternative dispute resolutionPsychology

Abstract

fetched live from OpenAlex

Abstract Can judicial mediation within a settler state's justice system improve the experience of dealing with child welfare services for Indigenous parents? Interviews with social workers, lawyers, and judges in the Canadian province of Quebec yield little basis for optimism. Adapting judicial mediation will not suffice to decolonize dispute resolution between Indigenous individuals and the state. Mediation fits uneasily with the severe power disparity in this setting. Moreover, the cautious nature of participants’ recommendations signals the limited adaptive capacity of the settler state's system of civil justice. The recommendations exemplify relatively superficial accommodation, rather than deep engagement with legal pluralism and Indigenous difference. Constraints on the state system's ability to adapt are both legal and cultural. This study contributes to literatures on Indigenous and colonial legal cultures in relation to child welfare, on access to justice for Indigenous peoples, and on mediation in Canada and elsewhere.

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)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.351
Threshold uncertainty score0.698

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.008
Scholarly communication0.0040.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.010
GPT teacher head0.276
Teacher spread0.266 · 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 designQualitative
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

Citations5
Published2022
Admission routes2
Has abstractyes

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