Tourism, land tenure transformations, and territorial dynamics on the Amborovy coastline, Mahajanga, Madagascar
Bibliographic record
Abstract
The Amborovy coastline, located in Mahajanga on Madagascar’s north-west coast, has undergone accelerated land-tenure change driven by tourism growth. The expansion of tourism infrastructure since 2000 has triggered intense competition for coastal land – amounting to a veritable rush to the shoreline. This pressure, coupled with aggressive real-estate speculation, has intensified conflicts between tompon-tany (local customary rights-holders) and investors, while undermining coastal ecosystems. Grounded in legal pluralism and multiscalar governance frameworks, this article assesses the effectiveness of Madagascar’s 2005 land reform, with particular attention to Propriété Privée Non-Titrée (PPNT; “untitled private property” mechanism), in the context of accelerated coastal commodification. A mixed-methods design combines diachronic GIS-based mapping with fieldwork conducted in 2023-2024, documenting changes in the built environment since the 1980s. Findings indicate that, despite the innovative intent of PPNT, natural and agricultural areas have been rapidly converted into tourism and real-estate developments since 2010, often under the control of extra-local investors. In this north-western region, reforms have not prevented the marginalisation of local populations nor environmental degradation. Preventing territorial fragmentation in Mahajanga therefore requires urgently implemented adaptive governance, combining the institutional recognition of customary rights with effective regulation of land markets to curb speculation. Such normative hybridisation is critical to prevent Amborovy from becoming an experimental epicentre of socio-spatial fragmentation.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".