Towards a Broader Perspective on Tourism Education, Research and Publication
Bibliographic record
Abstract
Purpose. The aim of the study is to discuss tensions between the academic responsibilities of education, research and publication, and how these have made tourism academia increasingly inward-focused. Method. Drawing upon approximately 50 years of personal experiences as an academic based in a faculty of environment. Findings. Tourism research has become more and more insular, reducing opportunities to contribute to the resolution of important public debates and policy issues, undermining enhancement of the reputation of the field and those involved in it. Research and conclusions limitations. The limitations include lack of a literature review or structured empirical research. It is concluded that tourism scholarship should be broadened and engage more with other fields and disciplines. Practical implications. Tourism curricula should be broadened, while administrative procedures should be more flexible to facilitate the creation of greater synergies between teaching, research and publication. Originality. In the manuscript, topics are addressed that are of great interest and often discussed informally, but are seldom put in writing. Type of paper: An opinion piece.
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.
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 | 0.051 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.009 | 0.054 |
| Scholarly communication | 0.042 | 0.039 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.014 | 0.013 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".