Landmines and Local Community Adaptation
Notice bibliographique
Résumé
Despite international mobilization for greater humanitarian mine action and despite considerable clearance achievements, the majority of mine‐affected communities have not yet been involved in formal clearance activities. They adapt to the contamination largely by local means. The differing degree to which local adaptation is successful is now better understood as a result of the Global Landmine Survey, a multi‐country survey project launched in the wake of the 1997 Ottawa treaty to ban anti‐personnel mines. Socio‐economic impact surveys have since been completed in several countries. In addition to landmines, the Global Landmine Survey records impacts also from unexploded ordnance (UXO). The ability to avoid mine incidents is used to measure adaptation success. We use a variant of Poisson regression models in order to identify community and contamination correlates of the number of recent landmine victims. We estimate separate models using data from the Yemen, Chad and Thailand surveys. We interpret them in a common framework that includes variables from three domains: Pressure on resources, intensity of past conflict and communities’ institutional endowments. Statistically significant associations occur in all three domains and in all the three countries studied. Physical correlates are the most strongly associated, pointing to a lasting deadly legacy of violent conflict, but also significant learning effects over time are present. Despite different measurements of institutional endowments, in each country one factor signifying greater local development is correlated with reductions in victims, whereas factors commonly associated with the presence of government officials do not contribute to local capacity to diminish the landmine problem. Strong spatial effects are manifest in clusters of communities with recent victims. Two policy consequences emerge. Firstly, given humanitarian funding limits, trade‐offs between clearing contaminated land and creating alternative employment away from that land need to be studied more deeply; the Global Landmine Survey will need to reach out to other bodies of knowledge in development. Secondly, communities with similar contamination types and levels often form local clusters that are smaller than the administrative districts of the government and encourage tailored planning approaches for mine action. These call for novel coalitions that bring advocacy and grassroots NGOs together with local governments, agricultural and forestry departments and professional mine clearance and awareness education agencies.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».