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Record W2022270750 · doi:10.1080/01459740802427729

Nerves as Embodied Metaphor in the Canada/Mexico Seasonal Agricultural Workers Program

2008· article· en· W2022270750 on OpenAlexafffundabout
Avis Mysyk, Margaret England, Juan Arturo Avila Gallegos

Bibliographic record

VenueMedical Anthropology · 2008
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsUniversity of WindsorCape Breton University
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorUniversity of SydneyCape Breton University
KeywordsEmbodied cognitionMedicalizationContext (archaeology)MetaphorDistressResistance (ecology)PsychologyPsychiatryClinical psychologyHistoryEcology

Abstract

fetched live from OpenAlex

This article examines nerves among participants in the Canada/Mexico Seasonal Agricultural Workers Program (C/MSAWP). Based on in-depth interviews with 30 Mexican farm workers in southwestern Ontario, we demonstrate that nerves embodies the distress of economic need, relative powerlessness, and the contradictions inherent in the C/MSAWP that result in various life's lesions. We also explore their use of the nerves idiom as an embodied metaphor for their awareness of the breakdown in self/society relations and, in certain cases, of the lack of control over even themselves. This article contributes to that body of literature that locates nerves at the "normal" end of the "normal/abnormal" continuum of popular illness categories because, despite the similarities in symptoms of nerves among Mexican farm workers and those of anxiety and/or mood disorders, medicalization has not occurred. If nerves has not been medicalized among Mexican farm workers, neither has it given rise to resistance to their relative powerlessness as migrant farm workers. Nonetheless, nerves does serve as an effective vehicle for expressing their distress within the context of the C/MSAWP.

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 score0.644
Threshold uncertainty score0.709

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.015
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0010.002
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 head0.021
GPT teacher head0.319
Teacher spread0.298 · 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

Citations26
Published2008
Admission routes3
Has abstractyes

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