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Record W4390490957 · doi:10.31542/1kg5j028

Distorted Perceptions of Corporate Harm in Comparison to Crime

2023· article· en· W4390490957 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCrossing Borders Student Reflections on Global Social Issues · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Conservation and Criminology Analyses
Canadian institutionsMacEwan University
Fundersnot available
KeywordsHarmArgument (complex analysis)Compensation (psychology)Construct (python library)Scope (computer science)Criminal justiceFoundation (evidence)Economic JusticeLaw and economicsPerceptionCriminologyPolitical scienceBusinessPsychologySocial psychologyLawSociologyComputer scienceMedicine

Abstract

fetched live from OpenAlex

This paper poses a critical analysis of the Worker’s Compensation Act, providing a foundation for the argument that crime is a social construct and therefore, is incapable of considering various aspects of corporate harm. Worker’s Compensation Board Appeals are examined to demonstrate the limits of the current state of the Worker’s Compensation Act, pointing specifically to harms that originate from workplace fatalities, long-term illnesses, and threats to mental health. The overall argument contends that we should move away from the narrow scope of the current definition of crime and seek a harm-based approach that allows for the consideration of multiple harms, which are often obscured by the criminal justice system.

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.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.771

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
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 head0.125
GPT teacher head0.473
Teacher spread0.348 · 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