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Record W2789240533 · doi:10.12735/jfe.v9n1p26

The Influence of Financial Status on the Safety Performance of Regulated Companies: The Role of Enforcement

2018· article· en· W2789240533 on OpenAlexvenueno aff
Dietrich Earnhart, Kathleen Segerson

Bibliographic record

VenueJournal of Finance & Economics · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicRegulation and Compliance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEnforcementBusinessFinanceAccountingPolitical scienceLaw

Abstract

fetched live from OpenAlex

A better understanding of the link between a firm’s financial status and its regulated performance can help to improve the design of regulatory regimes and lead to more efficient regulatory structures. To date, however, the literature investigating this link has not considered the role that regulatory enforcement plays in determining how financial status affects performance. This paper analyzes how regulatory enforcement affects the relationship between financial status and the safety performance of regulated firms. It examines a particular form of safety performance, namely, the environmental performance of companies regulated under environmental protection laws. In particular, our study explores this effect in the context of the regulation of water pollution using data on wastewater discharges from U.S. chemical manufacturing facilities for the years 1995 to 2001. The results suggest that enforcement in general can play an important role in shaping the effects of financial status on safety performance.

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)0.024
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.200
Teacher spread0.190 · 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 designObservational
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

Citations0
Published2018
Admission routes1
Has abstractyes

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