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Record W2994256005 · doi:10.1017/9781108694469.005

How Lower Courts Respond to a Change in a Legal Rule

2019· book-chapter· en· W2994256005 on OpenAlexaffabout
Anthony Niblett

Bibliographic record

VenueCambridge University Press eBooks · 2019
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicLaw, Economics, and Judicial Systems
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLawCourt of recordRemand (court procedure)Tax courtLaw of the casePolitical scienceCourt of equityCourt decisionOriginal jurisdictionJurisdictionSupreme court

Abstract

fetched live from OpenAlex

We investigate how lower courts respond to a change in the legal rule by an appellate court. We create a dataset comprising 525 cases from the Tax Court of Canada over the period 1997 to 2017 that determine whether a worker is an employee or an independent contractor for tax purposes. We look at how this lower court responds to a 2006 decision by the Federal Court of Appeals introducing a new factor in a multi-factor test to be applied by the lower court. We find only limited evidence that this change in the legal rule has any impact upon the outcomes of lower court cases.

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)0.015
metaresearch head score (Gemma)0.111
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.147
Threshold uncertainty score0.293

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.111
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0030.003
Scholarly communication0.0100.003
Open science0.0020.002
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0100.002

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 head0.038
GPT teacher head0.189
Teacher spread0.151 · 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
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
Published2019
Admission routes2
Has abstractyes

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