Le développement communautaire local et le tourisme communautaire : une analyse conceptuelle comparative
Bibliographic record
Abstract
Resume : Selon les auteurs de l'article, le tourisme de masse ne contribue pas au developpement local des communautes, mais plutot les devitalise. Cet article propose une recension des ecrits concernant l'approche du tourisme communautaire et celle du developpement local communautaire afin d’etablir les liens entre elles et de montrer que le tourisme communautaire peut etre une forme privilegiee de developpement local. Il explique en quoi les convergences entre ces deux approches peuvent servir de point de depart pour elaborer une conception du tourisme communautaire susceptible de contribuer a contrer les processus de devitalisation et d’appauvrissement qui caracterisent certaines communautes hotes. Mots-cles : tourisme communautaire, developpement communautaire local, initiative locale Abstract: According to the authors of this paper, mass tourism does not generate the development of local communities but rather their devitalization. This paper presents a cross-literature survey on community-based tourism and local community development. It proposes some links between these two approaches and asserts that community-based tourism can be a strategy to trigger local community development. It address the conditions under which the convergence of these two approaches may allow the launching of development initiatives liable to counter the devitalization and impoverishment process which characterizes certain mass tourism oriented places. Keywords: community-based tourism, community local development, local initiative
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".