A survey of doctoral theses accepted by universities in the UK and Ireland for studies related to tourism, 1990-1999
Bibliographic record
Abstract
The Index of Theses provided the single source for multiple searches utilizing the following key words: ‘holiday’, ‘holidaymaker’, ‘holidays’, ‘tourism’, ‘tourist’, ‘tourists’, ‘travel’, ‘visitor’ and ‘visitors’. A refined list of 149 doctoral theses accepted by universities in the UK and Ireland between 1990 and 1999 is reported. Results of the survey are reported for awarding university and year of acceptance, subject categories, location of fieldwork and methods of data collection and analysis. The universities of Strathclyde and Surrey accepted just over a quarter of all theses in the reported period. The frequency of accepted theses rose from four in 1990 to 29 in 1997 with a mean yearly average since 1996 of 23. Twenty-two subject categories were created. Four frequent areas of study were reported; development, impact, behaviour and industry and these accounted for approximately half of the theses. Fieldwork locations were spread across the major regions of the world with studies of the UK comprising less than a quarter of the theses. The analysis of methods confirms the prevailing influence of positivist (questionnaire) and hermeneutic (interview) epistemologies in these studies of tourism.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".