MétaCan
Menu
Back to cohort
Record W2957568653 · doi:10.3138/utlj.2018-0022

Unity in the eye of the beholder? Reasons for decision in theory and practice in the Ontario Works program

2019· article· en· W2957568653 on OpenAlexaffvenueabout
Jennifer Raso

Bibliographic record

VenueUniversity of Toronto Law Journal · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicJudicial and Constitutional Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsScholarshipCorporate governanceFront linePublic relationsScale (ratio)Judicial opinionPolitical scienceSociologyLawManagementEconomicsGeography

Abstract

fetched live from OpenAlex

This article interrogates reasons for decision, a central concept in Canadian public law scholarship. Using spatiotemporal scale as an analytical tool, it shows how unified reasons may be more easily recognized at the scale of judicially reviewable administrative decisions common to public law scholarship, yet elusive at the scale of front-line decision making. It then investigates how a variety of mechanisms, including data entries and notes, function together behind the front lines of social assistance agencies in the province of Ontario. Drawing on qualitative research into caseworkers’ decision-making practices, this article illustrates how the ‘reasons’ for a particular administrative decision may be multiplied and fractured across software programs, emails, and physical case files. Further, it demonstrates how notes are both more and less than reasons. As they perform three internal communicative tasks central to administrative governance – recording evidence, explaining decisions, and justifying potentially contentious outcomes to other administrative insiders – notes facilitate decision-making practices that ensure institutionally acceptable outcomes are reached, even as one note may not fully capture the logic underlying a particular decision. Ultimately, this article aims to motivate theoretically inclined legal scholars to reconsider the concept of reasons for decision in light of the decision-making practices of front-line administrators.

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)0.000
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 score0.695
Threshold uncertainty score0.395

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 head0.019
GPT teacher head0.297
Teacher spread0.277 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations8
Published2019
Admission routes3
Has abstractyes

Explore more

Same venueUniversity of Toronto Law JournalSame topicJudicial and Constitutional StudiesFrench-language works237,207