Canada's Seasonal Agricultural Worker Program: Capturing Ten Years of Advocacy with Framing Theory
Bibliographic record
Abstract
Canada's agricultural sector has been facing a chronic labour shortage for over a century. To counter this shortage Canada introduced the Temporary Foreign Worker Program (TFWP) in the 1960's, bringing in workers from abroad for assistance. Some describe the program to be a "win-win- win" situation for the workers, farmers and involved nations alike, however critics and the data challenge that notion. Numerous cases of migrant worker exploitation have drawn the interest of human right advocates, which have been advocating for change for decades. Using framing theory as conceptualized by Benford and Snow (2000) we delve into the political debate around what is now called the Seasonal Agricultural Worker Program (SAWP) in order to capture what are the frames of the major relevant stakeholder advocates and how different framing strategies are applied in hope to attain greater political will. We analyze these framings in parallel with the political climate, relevant recommendations made by standing committees of the Canadian House of Commons and legislative changes in order to capture how the dynamic frames of the Canadian Government on the SAWP have changed to resonate more or less with the other respective advocate framings between the years 2011 and 2022. A shift in response of the Canadian Federal...
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 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 | 0.028 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.016 |
| Science and technology studies | 0.046 | 0.050 |
| Scholarly communication | 0.021 | 0.009 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".