Investigating the Disclosure of Corporate Social Responsibility in International Hotel Chains
Bibliographic record
Abstract
This paper examines how international hotels communicate Corporate Social Responsibility (CSR) on their websites. In particular, this study employs a corpus-based discourse approach to investigate the content and language included in the CSR reports of two international hotel chains, Marriott and Hilton. The aim is to understand the type of information reported as well as the discursive strategies employed to promote CSR performance with regards to economic, social, and environmental issues. The findings reveal several common themes in Marriott and Hilton’s CSR reports, highlighting their commitment to sustainability, ethical behavior, and community involvement. The importance of diversity and inclusion, organizational supervision, and responsibility is emphasized in the reports. Both hotel chains prioritize supporting local communities and upholding social responsibility through charitable efforts and leadership development programs. Environmental sustainability is a key focus, with efforts to adopt sustainable practices in an attempt to achieve long-term environmental goals. Further research will include a wider range of international hotel chains and incorporate social media analysis to provide a more comprehensive understanding of CSR practices in the hospitality and tourism industry.
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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 | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".