All hands on deck: Agricultural labour in British Columbia and Nova Scotia
Bibliographic record
Abstract
Canada is experiencing an agricultural labour shortage that will contribute to economic and food-security challenges if left unchecked. This qualitative study explores how horticultural farm owners and operators in British Columbia and Nova Scotia perceive domestic workers, temporary foreign workers, and labour-saving technologies in meeting growing labour demands. Seven semi-structured interviews were conducted over Zoom, from February to April 2022, with farmers from both provinces. A thematic analysis was conducted, and eight predominant themes were identified from the interviews. These themes included the nature of the work, the perceived nature of the workers, the role of technology in meeting labour demands and increasing efficiency, strategies for successful labour planning, consumer perceptions of and interest in farming, farmer values and job satisfaction, external challenges impacting labour, and other opportunities being pursued by farmers. From this research, four broad categories of recommendations were proposed to support horticultural farmers in recruiting and retaining domestic workers, temporary foreign workers, and in adopting and implementing labour-saving technology.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".