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Record W1508286664 · doi:10.60082/2817-5069.2791

No Lawyer for a Hundred Miles?: Mapping the New Geography of Access of Justice in Canada

2015· article· en· W1508286664 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueOsgoode Hall law journal · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicOccupational and Professional Licensing Regulation
Canadian institutionsUniversity of TorontoDalhousie University
Fundersnot available
KeywordsEconomic JusticeScope (computer science)Distribution (mathematics)LocalityPolitical scienceLegal educationLegal professionLegal serviceRural areaLawGeographyPublic relationsSociologyPublic administration

Abstract

fetched live from OpenAlex

Recent concerns about the geography of access to justice in Canada have focused on the dwindling number of lawyers in rural and remote areas, raising anxieties about the profession’s inability to meet current and future demands for localized legal services. These concerns have motivated a range of policy responses that aim to improve the education, training, recruitment and retention of practitioners in underserved areas. We surveyed lawyers across Ontario to better understand their physical proximity to clients and how, if at all, that proximity promotes access to justice. We find that lawyers’ scope of practice varies based on a number of factors, and in several areas of law lawyers serve clients beyond their immediate locality. Our results suggest that debates about the geography of access should be premised on the goal of territorial justice as an equitable distribution of legal services rather than a narrower emphasis on the equal distribution of lawyers.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.444
Threshold uncertainty score0.247

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.112
GPT teacher head0.266
Teacher spread0.154 · 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