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Record W1514583382

A Counter-pedagogy for Social Justice: Core Skills for Community Lawyering

2002· article· en· W1514583382 on OpenAlexaff
Shin Imai

Bibliographic record

VenueeYLS (Yale Law School) · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Education and Practice Innovations
Canadian institutionsYork University
Fundersnot available
KeywordsMainstreamLegal educationCurriculumClass (philosophy)Political sciencePedagogySociologyIdentity (music)Legal professionEconomic JusticePublic relationsLaw
DOInot available

Abstract

fetched live from OpenAlex

An important component of lawyering for social justice is working in communities. In addition to conventional skills, such as legal analysis and litigation, community-based lawyers need skills not taught in the mainstream curriculum. This article describes a counter-pedagogy for teaching students three core skills for community lawyering: how to collaborate with members of the community, how to acknowledge personal identity, race and emotion, and how to take a community perspective on legal problems. The author argues that these skills cannot be taught in isolation, but should be integrated into the teaching itself, including the teaching of substantive areas of the law. He suggests, for example, that students are more likely to learn how to collaborate if the entire clinical course is based on a collaborative approach, rather than having a special class dedicated to collaboration. The article includes descriptions of techniques and exercises used at Osgoode Hall Law School in the Intensive Programme on Poverty Law at Parkdale Community Legal Services and in the Intensive Programme in Aboriginal Lands, Resources and Governments.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.801
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.102
GPT teacher head0.416
Teacher spread0.315 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations6
Published2002
Admission routes1
Has abstractyes

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