Global tourism in crisis: conceptual frameworks for research and practice
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 The aims of this Editorial are twofold: (i) synthesise emergent themes from the special issue (ii) tender four theoretical frameworks toward examination of crises in tourism. Design/methodology/approach The thematic analysis of papers highlights a diversity of COVID-19 related crises contexts and research approaches. The need for robust theoretical interventions is highlighted through the four proposed conceptual frameworks. Findings Crises provides a valuable seam from which to draw new empirical and theoretical insights. Papers in this special issue address the unfolding of crises in tourism and demonstrate how its theorization demands multi and cross-disciplinary entreaties. This special issue is an invitation to examine how global crises in tourism can be more clearly appraised and theorised. The nature of crisis, and the extent to which the global tourism community can continue to adapt remains in question, as dialogues juxtapose the contradictions between tourism growth and tourism sustainability, and between building back better and returning to normal. Originality/value The appraisal of four conceptual frameworks, little used in tourism research provides markers of the theoretical rigour and novelty so often sought. Beck’s risk society reconceptualises risk and the extent to which risk is manmade. Biopolitics refers to the power over the production and reproduction of life itself, where the political stake corresponds to power over society. The political ecology of crisis denaturalises “natural” disasters and their subsequent crises. Justice complements an ethic of care and values like conative empathy to advance social justice and well-being.
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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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