The cost of your organic blueberries: A look on how vulnerable migrant workers in Canada are being impacted during the COVID-19 pandemic
Bibliographic record
Abstract
The media has covered the working conditions of Migrant Workers in Canada during the Covid-19 pandemic, seemingly attentive to the temporary scarcity of food; this scarcity seems to have made people more aware of the food supply chain, and thus brings attention to an overlooked group of people, Migrant Workers. Using text-based public data this MRP seeks to answer the following question: How social actors are represented in the media and how those representations reflect the federal government policy and the experiences of the Migrant Workers? The research is conducted through a Critical Race Theory framework lens that will inform the analysis and discussion of this paper. The methodology chosen to discuss the representation of the social actors in the media is the Critical Discourse Analysis approach focusing on the representation of Social Actors as suggested by van Leeuwen (2008).
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.027 | 0.010 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".