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Record W4411244351 · doi:10.1080/00358533.2025.2498161

A comparison of farm stressors in the UK and Canada

2025· article· en· W4411244351 on OpenAlexafffundabout
Sarah Nyczaj Kyle, Emma Barkus, Stephen Dunne, Andria Jones‐Bitton

Bibliographic record

VenueThe Round Table · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Farm Safety
Canadian institutionsUniversity of Guelph
FundersAgriculture and Agri-Food Canada
KeywordsStressorPolitical scienceGeographyHistoryPsychology

Abstract

fetched live from OpenAlex

To understand the effects of stress on farmers, international data collection needs to be undertaken on a global level to enable cross-national comparisons, including across Commonwealth countries. An online survey compared farming stress in the UK and Canada (N = 569: 51% UK, 49% Canada). While finances were the primary stressor in both nations, Canadian farmers more frequently experienced stress from weather and labour management than UK farmers, who reported stress from animal health, farm/rural crime and isolation more often than their Canadian counterparts. Targeted interventions must address these contextual challenges. These findings support the newly developed ‘Interconnected Farm Stress Pyramid’ which provides insights into the synergistic nature of farm stressors. An integrated scale is now necessary to enhance understanding of the impact of stress experienced by Commonwealth farmers.

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)0.003
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 score0.039
Threshold uncertainty score0.284

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.008
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.238
Teacher spread0.223 · 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

Citations2
Published2025
Admission routes3
Has abstractyes

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