Territorial Diagnosis of Ecotourism in Tunisian Mountain Protected Areas: Stakeholders, Positions and Power Relations
Bibliographic record
Abstract
Since the 2000s, projects and studies have been multiplied for the development of ecotourism in Tunisian protected areas. Despite these efforts, the Tunisian case faces several failures. As part of this study, we aim to provide elements of reflection on a contractual scheme for a sustainable territorial development plan by ecotourism, around mountain protected areas in Tunisia. For this reason, we adopted the strategic prospective analysis revealing and analyzing the relationships between the different actors involved in ecotourism in the protected area. A Matrix of Alliances, Conflicts, Tactics and Objectives among MACTOR actors was developed in a participatory way to analyze the actors' strategies. After doing a triangular analysis which consists in to an inventory of the projects and studies about the protected area of Ichkeul and Cape Negro-Jbel Chitana, semi-structured interviews with personals from different sectors, we invited the actors met on the field or mentioned in the projects in a workshop organized in partnership with the General Directorate of Forests in Tunis in order to identify the different categories of actors and analyze the balance of power between them. This analysis is done through a matrix notation system. Eight categories of actors have been identified: international cooperation, resource managers, politic policy etc. Thanks to the matrix notation systems, we have been able in a participative way to classify these eight categories of actors into four types: dominant actors, relay actors, autonomous actors and dominated actors. Thus, the MACTOR method allowed us to identify actors who played a role in the development of ecotourism projects in Tunisia and to be able to diagnose their balance of power. This allowed showing the multidisciplinarity and complexity of the sector as well as the strong influence of certain actors such as international cooperation and public decision-makers. To conclude, the MACTOR analysis of the ecotourism actors in the protected area of Ichkeul and Cap Negro-Jbel Chitana enters into a methodology of prospective territorial analysis in this area to understand the points that caused the failure of several experiments.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".