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Record W7048128774

Infringement Notices: Stimulus for Prevention or Trivialising Offences?

2015· article· en· W7048128774 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueANU Open Research (Australian National University) · 2015
Typearticle
Languageen
FieldEngineering
TopicPhotocathodes and Microchannel Plates
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionGestational periodHyporeflexiaTSG101DiafiltrationDysgeusiaPretextArticular cartilage damageProteogenomics
DOInot available

Abstract

fetched live from OpenAlex

In the OHS field increasing use is being made of administrative penalties to enforce OHS legislation. Infringement notices (also known as penalty notices or on-the-spot fines) are used in several Australian jurisdictions and there are plans to introduce them in others. Overseas jurisdictions with some form of OHS administrative penalty include the United States, some Canadian provinces, and the system recently enacted in New Zealand. This article reviews empirical evidence and legal argum ents about the use of infringement notices for enforcing OHS legislation. Key factors influencing the impact of these notices are discussed, including the monetary amounts of penalties, the nature of offences, the criteria and processes for issuing notices, and other implementation issues. There is a need for further empirical studies to determine the characteristics of infringement notice schemes that are most effective in motivating preventive action.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.225
Threshold uncertainty score0.390

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.386
GPT teacher head0.417
Teacher spread0.031 · 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