All Play and No Work: The Case of Revitalizing Career Perceptions in Canada’s Tourism Industry
Bibliographic record
Abstract
This case analyzes the challenges facing the Canadian tourism industry workforce following the COVID-19 pandemic, fueled by perceptions of careers in the tourism industry as temporary, low-wage, and unsatisfactory for long-term prospects. According to Tourism HR Canada, a pan-Canadian organization focused on supporting the recovery and growth of the Canadian tourism industry, these declines have created significant challenges for employers struggling to recruit and retain employees. This case study aims to equip students with the necessary tools to analyze data collected by Tourism HR Canada and its partners to identify Canadians’ perceptions of jobs in the tourism industry and develop actionable recommendations for tourism employers. Students will use this data to uncover patterns in the provided data and compare their findings across different contexts, with the ultimate goal of developing a robust Strengths, Weaknesses, Opportunities, and Threats (SWOT) Analysis to transform the public’s perceptions and reshape the Canadian tourism workforce.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.055 | 0.017 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.004 | 0.007 |
| 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".