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Record W2983158694 · doi:10.1177/1743872119886235

Law and Humanities: A Field Without a Canon

2019· article· en· W2983158694 on OpenAlexaffabout
Sara Ramshaw

Bibliographic record

VenueLaw Culture and the Humanities · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Education and Practice Innovations
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsThe artsScholarshipHumanitiesDisciplineSociologyField (mathematics)LawPolitical scienceArt

Abstract

fetched live from OpenAlex

This short Commentary imagines law and humanities not as a “canon” per se, but as a “field without a canon”; or a canon that resists canonization. Arts-based practices utilized in legal research and teaching expose the law and humanities “canon” to its dual (and somewhat contradictory) nature: ever straining toward a preestablished archive, it must also leap ahead fearlessly to properly defy disciplinary boundaries and move the field beyond siloed thinking, which is one of the preliminary aims of law and humanities scholarship and pedagogy. Arts-based practices consist not of a stable collection of set texts but instead signify a process of experimentation that is ever in flux and alive to possibility. It is this process of discovering new arts-based practices that ensures law and humanities remains a vibrant, yet ever-changing, field for years to come. To that end, this Commentary surveys a sampling of outsider approaches to law and humanities scholarship and pedagogy, those more concerned with process than product, and which are coming from outside of or beyond the more traditionally conceived canon of law and humanities. These approaches fall into two broad categories: (1) arts-based scholarly legal practices and (2) arts-based legal pedagogical practices. A uniting feature of both these approaches is that they are being undertaken and explored by Canadian legal scholars at a small law school on Vancouver Island on the West Coast of Canada, namely the University of Victoria Faculty of Law, where there is an impressive number of faculty members using arts-based practices in their research and teaching.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.898
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.001
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 head0.036
GPT teacher head0.317
Teacher spread0.282 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations2
Published2019
Admission routes2
Has abstractyes

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