The Tripartite Bargaining Model: The Struggle to Organise Migrant Farmworkers
Bibliographic record
Abstract
This dissertation analyses the issues concerning strategies for improving the working and living conditions of migrant farmworkers in the United States and Canada. By comparing the tripartite and sharecropping models in commercial agriculture, it is demonstrated that unionisation and three-way collective bargaining are efficient and proven techniques for increasing workplace standards for migrant farmworkers. The tripartitc model separates agriculture into three discernable actors: food corporations, growers and farmworkers. While some agricultural sectors are dominated by corporate entities which combine both production and processing operations, other sectors such as cucumbers and tomatoes are characterised by large processing corporations which are supplied by commercial growers. Without the presence of food corporations in collective bargaining, many growers are unable to provide for better working conditions for migrant farmworkers. The Farm Labor Organizing Committee (FLOC) has significantly established the only tripartite labour relations framework in North American agriculture. FLOC has used commercial boycotts for more than two decades, in order to pressure food corporations to participate in collective bargaining with migrant farmworkers. The union is presently conducting a national boycott of the Mt. Olive Pickle Company in North Carolina, a campaign which aims to bring the company to the bargaining table and to put an end to the sharecropping model in the state's cucumber industry.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".