Climate Change and Labour Union Strategy in the Accommodation Sector: Opportunities and Contradictions
Bibliographic record
Abstract
Climate change is affecting tourism-related industries such as accommodation and hospitality (e.g., changes in tourist flows, the ‘greening’ of hotels). The role organized labour in such industries will play in climate change mitigation and adaptation is less studied. This paper explores how such responses may be integrated into recent strategic initiatives building labour union capacities in the accommodation sector. The case of UNITEHERE, a union representing over 100,000 hotel workers in the United States and Canada, is explored. Specific attention is given to the integration of climate change into current activities such as: the union’s fight against ‘green-washing’; the scaling up of collective bargaining; the use of consumer preference as leverage against hotel companies; the implementation of a ‘high road vision’ for the sector; and campaigns for accessible public transit and community economic development. The paper concludes that climate change will be incorporated into existing union strategies, but there is limited capacity for radical transformation of the sector practices.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".