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Record W4413186528 · doi:10.32920/29896172.v1

Looking at Legal Ethics Through the Lens of Family Violence

2025· preprint· en· W4413186528 on OpenAlexaboutno aff
Deanne Sowter

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicLegal Education and Practice Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsLens (geology)Through-the-lens meteringLegal ethicsSociologyPolitical scienceCriminologyLawOpticsPhysics

Abstract

fetched live from OpenAlex

The words “family violence”, “domestic violence”, “intimate partner violence” and “coercive control” do not appear anywhere in the Federation of Law Societies of Canada Model Code of Professional Conduct. The Code does not typically have special rules for special areas of practice, but family violence is not strictly a family law matter. Family violence can be an issue in immigration and refugee law, employment law, corporate law, criminal law, landlord-tenant law, and real estate law, to name a few. When family violence is overlooked, the absence of recognition can perpetuate harm through the justice system. Family violence is a people issue and anywhere there are people they may be experiencing family violence. Legal ethics crosses all areas of legal practice, dealing with people, so it follows that legal ethics issues also intersect with family violence. In this post, I suggest that we ought to think about family violence as a legal ethics issue, and as such, we ought to think about the lawyer’s role and her professional obligations through the lens of family violence.

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)0.007
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.075
Threshold uncertainty score0.181

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0190.087
Scholarly communication0.0140.011
Open science0.0020.005
Research integrity0.0080.012
Insufficient payload (model declined to judge)0.0040.000

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 head0.170
GPT teacher head0.468
Teacher spread0.298 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2025
Admission routes1
Has abstractyes

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