MétaCan
Menu
Back to cohort

Des technologies et des destinations touristiques intelligentes : entre rhétorique et expérimentation

2022· article· fr· W4280615127 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueÉtudes caribéennes · 2022
Typearticle
Languagefr
FieldEngineering
TopicSmart Cities and Technologies
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsHumanitiesPolitical scienceTourist destinationsTourismDestinationsPhilosophy

Abstract

fetched live from OpenAlex

Réseaux intelligents, destinations intelligentes, villes intelligentes…. sont des concepts qui ont le vent en poupe ces dernières années. Ils sont les composantes d’une rhétorique qui prônent des idéaux technos/éco systémique à travers le déploiement des technologies dites « intelligentes », de la gestion optimisée de l’énergie, pour in fine prétendre participer à l’amélioration de la qualité de vie des résidents et des touristes. Cette contribution a pour objet de mettre en perspective les transformations que connaissent les villes et les destinations touristiques à l’ère des transformations technologiques et managériales. Elle tente de proposer un regard croisé de la convergence entre le tourisme et les technologies d’information dans le cadre de la destination intelligente. Dans la seconde partie, nous présenterons succinctement les travaux sélectionnés pour ce numéro spécial de la revue Études Caribéennes.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.556
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.267
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it