La recherche en tourisme et les mesures de performance touristique post-COVID
Bibliographic record
Abstract
Les organismes de gestion de la destination, tel l’Office du tourisme de Québec, sont habituellement responsables de la recherche auprès des clientèles touristiques et de la mesure de performance de l’industrie touristique sur leur territoire. La crise actuelle de la COVID-19 chamboulera la plupart des projets en cours et ceux prévus pour les prochaines années. Les projets de recherche futurs devront être adaptés aux nouveaux besoins d’informations et aux habitudes et préférences des clientèles touristiques post-coronavirus. Pour ce qui touche aux mesures de performance, plusieurs facteurs modifieront les techniques et les méthodes de collecte, de compilation des résultats, ainsi que de diffusion des indicateurs de performance habituellement produits. Cet article présente les impacts qu’aura la crise actuelle sur les projets de recherche en tourisme et sur les mesures de performance d’une destination.
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 | 0.023 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".