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Record W4321367656 · doi:10.5304/jafscd.2023.122.004

Pathways for advancing good work in food systems: Reflecting on the international Good Work for Good Food Forum

2023· article· en· W4321367656 on OpenAlexaff
Susanna Klassen, Lydia Medland, Poppy Nichol, Hannah Pitt

Bibliographic record

VenueJournal of Agriculture Food Systems and Community Development · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsUniversity of British Columbia
FundersEuropean Regional Development FundCardiff University
KeywordsFood systemsWork (physics)Futures contractVisionPolitical scienceAgricultureFood securityAgroecologyNexus (standard)Food processingBusinessEconomic growthSociologyEconomicsGeographyEngineering

Abstract

fetched live from OpenAlex

The crucial roles that workers, especially seasonal and migrant workers, play in our food systems have come under renewed attention in recent years. The coronavirus pandemic resulted in food work­ers being recognized as critical or essential workers in many countries. In 2021, this coincided with the UN International Year of Fruits and Vegetables (IYFV), highlighting the importance of horticul­tural crops to healthy lives globally. Yet, workers’ quality of life in this most labor-intensive form of food production is often disregarded, or in the case of the UN IYFV, misconstrued. The agriculture-migration nexus—on which food systems depend—remains recognized as a challenge, yet there is limited debate about how it could be ameliorated and a lack of articulation of desirable alternatives. While alternative food and peasant movements propose food system transformation and alternative labor futures based on agroecology, labor lawyers and other advocates propose regula­tion and formalization of workplace regimes to ensure fair working conditions. Most recently, a third pos­sibility has emerged from agri-tech innovators: a techno-centric future with far fewer agricultural work­ers. These three archetypes of agricultural labor futures (agroecological, formally regulated, and techno-centric) have the potential to leave food scholars and activists without a unified, coherent vision to advance. Addressing this gap, this paper reports and builds on insights harvested from the international Good Work for Good Food Forum, organized by the authors with the aim of shaping consensus on positive visions for work in food systems. About 40 scholar-activists across three continents discussed the current challenges facing food workers and crafted a collective vision for good food work. This vision is documented in the form of nine principles supported by a framework of seven enabling pathways. We conclude by em­pha­sizing the need for a people-centered incor­poration of technology and a re-valuation of food workers’ contributions to global food systems. We offer the vision as a collective platform for action to advocate for and organize with workers in food systems.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.176
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.072
GPT teacher head0.260
Teacher spread0.188 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations15
Published2023
Admission routes1
Has abstractyes

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