Human capital challenges in the hotel industry of Canada: finding innovative solutions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose This paper aims to identify possible solutions to the current and persistent challenge of attracting and retaining qualified people to work in Canada’s hotel industry. The outlook for the industry is that a critical shortage of skilled workers will continue to exist for at least the next decade. Design/methodology/approach This paper draws on the perspectives of three academics and three industry practitioners in an effort to identify root causes and possible solutions. Canadian and international literature is reviewed to establish current practices and point to gaps to be filled to meet the market needs. Recommendations are categorized by industry and academic perspectives. Findings The Canadian hotel industry faces challenges in filling job vacancies and maintaining employees in their roles. It is important for industry and academia to work collaboratively to educate the general public on the rewards and benefits of working in the Canadian hotel industry. Practical implications Many concrete strategies are suggested that individual hotel operations and the industry as a whole can implement to improve their human resource management and to entice potential employees to join the sector. Originality/value This paper adds value and contributes to the Canadian hotel industry and academia, as it represents current research and thought processes from both the academic community and the Canadian hotel industry.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it