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Restructuring, Environmentalism and the Problem of Farm Safety

2007· article· en· W2051529588 on OpenAlexaffabout
Alan Hall

Bibliographic record

VenueSociologia Ruralis · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Farm Safety
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsRestructuringBusinessGovernment (linguistics)Occupational safety and healthProduction (economics)PerceptionEnvironmentalismFarm workersPublic economicsMarketingAgriculturePoliticsEconomicsPolitical sciencePsychologyFinanceGeography

Abstract

fetched live from OpenAlex

Abstract This article examines the health and safety perceptions and practices of conventional, no till and organic grain farmers in Ontario Canada. Based on 12 intensive case studies, the analysis examines whether different restructuring and environmental orientations are related to different approaches to occupational health and safety. The analysis suggests that although there is a substantial level of awareness and knowledge of health and safety hazards among all the farmers, significant differences in practices are linked in complex and somewhat unexpected ways to the production and environmental approaches of the farmers. In particular, while economic constraints and rationales provide an overriding basis for risk‐taking across all the farmers, the level and form that this takes is shaped by farmer orientations to farm management and the environment. The article also links both the common patterns and variations in farmer practices to corporate and government discourses on the prevention of environmental and occupational injuries, suggesting that mixed messages undermine any effort to intensify farmer commitment to safety.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.675
Threshold uncertainty score0.654

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0070.017
Scholarly communication0.0030.001
Open science0.0000.002
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 head0.007
GPT teacher head0.196
Teacher spread0.189 · 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 designQualitative
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

Citations7
Published2007
Admission routes2
Has abstractyes

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