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Record W1597645875

The Psychology of Good Character

2010· article· en· W1597645875 on OpenAlexaffabout
Alice Woolley, Jocelyn Stacey

Bibliographic record

VenueeYLS (Yale Law School) · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Education and Practice Innovations
Canadian institutionsUniversity of British ColumbiaUniversity of Calgary
Fundersnot available
KeywordsCharacter (mathematics)Relevance (law)PaceContext (archaeology)Psychological researchPsychologyProcess (computing)Social psychologyEpistemologyLawPolitical scienceComputer sciencePhilosophy
DOInot available

Abstract

fetched live from OpenAlex

This paper explores the significance of the changing nature of the good character requirement for law society admission in Canada. It posits that good character has shifted from a philosophical concept into a psychological concept, with evidence of past bad acts claimed to be relevant for whether an applicant represents a future risk to the public. This shifting conception of character has, however, been only partial, and the decision-making processes of Canadian law societies have not kept pace with it. Instead, the decision-making process defines character generally and generically, with only occasional emphasis on character as a relevant predictor of future behaviour. In addition, law societies only rarely employ psychological evidence in their decision-making processes, and when they do employ such evidence seem uncertain as to its relevance and utility. The paper examines whether law societies should embrace a more overt recognition of character as a psychological concept. It reviews how psychological evidence is used in the context of determinations of custody and dangerousness, and the success (or, as it turns out, the failure) of psychological evidence as an aid to fair and accurate decision-making in those circumstances. In the end, the paper concludes that while treating good character as a psychological standard is the only way to make the requirement logical and justifiable in light of the purposes it is said to fulfill, the employment of a psychological standard is fraught with difficulty. There is, in the end, no reason to believe that a psychology based approach will lead to more coherent and fair decision-making. Given that, and given the significant issues with a non-psychological concept of character, the case for retaining a good character requirement for bar admission is weak.

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)0.004
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: Other · Consensus signal: Other
Teacher disagreement score0.104
Threshold uncertainty score0.206

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.067
Scholarly communication0.0070.004
Open science0.0010.005
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.368
Teacher spread0.340 · 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
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

Citations0
Published2010
Admission routes2
Has abstractyes

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