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Record W7029968741

The Mismatch Hypotheses in Law School Admissions

2014· article· en· W7029968741 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Education and Practice Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsGraduation (instrument)AttendanceAffirmative actionEliteEducational attainmentWhite (mutation)Ethnic groupQuarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

The match effects for five different student populations Native American Asian Black Hispanic and White are gathered and analyzed to determine whether these effects provide support for the match hypotheses with respect to law school grades graduation and bar passage While some evidence was found supporting the negative match hypothesis for Black and Asian law school students in the lower propensity range the match effects for bar passage in the upper range were much lower than Richard SanderÔÇÿs reports and did not approach statistical significance Moreover no negative match effects for graduation were apparent Thus the bar passage rates difference seems very modest relative to the substantial social networking advantages of elite school attendance Because the variables most strongly associated with higher levels of leadership are attainment of a bachelorÔÇÿs BA degree at Harvard Yale and Princeton and attainment of a law degree the implication is that leadership potential which may fall outside the bounds of traditional admission criteria is more suitably described as a benefit to society Even Sander noted that he did not consider perhaps the single greatest benefit of affirmative action in law school its role in building the longterm careers of Black lawyers placing them in the most elite ranks of the profession and American society

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)0.002
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.929
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.035
GPT teacher head0.338
Teacher spread0.303 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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

Citations2
Published2014
Admission routes1
Has abstractyes

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