MétaCan
Menu
Back to cohort
Record W2228579487

Blessings on the Food, Blessings on the Workers: Arts-based Education for Migrant Worker Justice

2013· article· en· W2228579487 on OpenAlexaffvenueabout
Deborah Barndt

Bibliographic record

VenueCanadian journal of environmental education · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsYork University
Fundersnot available
KeywordsMigrant workersEconomic JusticeThe artsSociologyWork (physics)AgricultureFood processingSocial justiceConsciousnessFood securityChild labourEconomic growthPolitical scienceSocial scienceEconomicsLawPsychologyGeography
DOInot available

Abstract

fetched live from OpenAlex

Migrant agricultural workers are not only on the margins of Canadian and global food systems; they are also on the margins of public consciousness about the labour behind the food we eat. Even local food movement groups who advocate for both social justice and sustainable food production have not made migrant labour a priority concern. Popular education, based on Freirean problem-posing methods and Gramscian notions of engaging contradictions, can use arts-based approaches to tap both minds and hearts in efforts to mobilize food activists to work for migrant worker justice. This essay examines the potential and limitations of an installation of Mexican-style altars, entitled “Local Food/Global Labour,” that aims to catalyze dialogue between food activists and labour activists around the issue of global migrant labour in local food production.

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)0.002
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: none
Teacher disagreement score0.982
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0120.011
Scholarly communication0.0040.003
Open science0.0010.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0110.001

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 head0.018
GPT teacher head0.208
Teacher spread0.191 · 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

Citations2
Published2013
Admission routes3
Has abstractyes

Explore more

Same venueCanadian journal of environmental educationSame topicOrganic Food and AgricultureFrench-language works237,207