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Record W2005639902 · doi:10.1080/09695958.2014.987780

The making of the Canadian legal profession: a hybrid heritage

2014· article· en· W2005639902 on OpenAlexaffabout
Philip Girard

Bibliographic record

VenueInternational Journal of the Legal Profession · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Education and Practice Innovations
Canadian institutionsYork University
Fundersnot available
KeywordsLegal professionCorporate governanceIndigenousLawLegal serviceAdversarial systemPower (physics)Political scienceInternational Legal English CertificateState (computer science)NeglectService (business)SociologyComparative lawManagementBusinessPsychology

Abstract

fetched live from OpenAlex

The Canadian legal profession emerged from the confluence of two distinct traditions: the American and the English. The colonies of British North America followed the pre-revolutionary American model of a unified legal profession, according to which all lawyers could practise as barristers and solicitors. American and Canadian lawyers pursued a client- and market-driven, eclectic type of practice that was receptive to innovations – such as the large law firm, the contingency fee, and university legal education – that were strongly resisted in England. On the governance side, however, Canadian lawyers created an indigenous but English-inflected model whereby professional self-governance was delegated to a statutorily-created body that had the power to compel all lawyers to join if they wished to practise law. With their commitment to client-centred service and strong governance, Canadian lawyers long enjoyed a cooperative and productive relationship with provincial governments, unlike the adversarial one characteristic of the United States or the long benign neglect of the legal professions by the English state. It is argued that this historical pattern may help to explain the continuing strength of the self-governance model in Canada at a time when it is being questioned and radically reformed elsewhere in the common law world.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.850
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.391
Teacher spread0.363 · 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

Citations5
Published2014
Admission routes2
Has abstractyes

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