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Record W7133024386

Bicycles traveling in the rain: A participatory, arts-informed account of Mexican farmworkers in Canada

2007· dissertation· W7133024386 on OpenAlexaboutno aff
Katie Marie Hinnenkamp

Bibliographic record

VenueTSpace · 2007
Typedissertation
Language
FieldAgricultural and Biological Sciences
TopicRural development and sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Work (physics)CommonwealthDramaGlobal South
DOInot available

Abstract

fetched live from OpenAlex

This participatory, arts-informed study examines the experiences of workers from Mexico that live and work in the Niagara-on-the-Lake region of Ontario, Canada under the Commonwealth Caribbean and Mexican Seasonal Agricultural Workers program (SAWP). Whereas previous literature on the experiences of SAWP workers has relied on researcher-driven interviews and observations, this study looks at how workers themselves choose to tell their stories using collage and drama in a series of interactive workshops. This document begins by outlining the research problem and goes on to review existing literature on guestworker programs like the SAWP and the global context surrounding them. An overview of the participatory, workshop methodology follows. Data collected in this study is then presented and analyzed, including a number of new findings. Finally, the effectiveness of the methodology is evaluated, along with recommendations for further research and community organizing with SAWP workers.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.113
Threshold uncertainty score0.235

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0440.009
Scholarly communication0.0050.001
Open science0.0020.006
Research integrity0.0020.003
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 head0.050
GPT teacher head0.341
Teacher spread0.292 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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