Modèle explicatif et interprétatifde l'anémie sévère(«Gbébile»)chezlessénoufodeKorhogo (Côte d'Ivoire)
Bibliographic record
Abstract
La santé mentale des agriculteurs semble être déterminante dans l’adaptation aux effets des changements climatiques. Cet article fait la synthèse des écrits existant sur la santé mentale, les facteurs qui y sont associés et l’adaptation des populations face aux effets des variabilités pluviométriques. Il vise à analyser la santé mentale avec ses déterminants pouvant influencer l’adaptation des producteurs aux chocs climatiques. Ce travail a été réalisé grâce à une recherche documentaire à l’aide des moteurs de recherche scopus, Google Scholar, Refseek, BASE, et Pubmed. Une série de documents scientifiques traitant des différentes thématiques en lien avec le sujet a été sélectionnée et fait objet de lecture et d’analyse minutieuse selon la méthode PRISMA 2020 statement et a permis de dégager les documents pertinents. Il a été également question de rechercher des approches théoriques qui ont permis de construire un cadre d’analyse théorique pouvant décrire les stratégies d’adaptation des agriculteurs dans un contexte de climat changeant. D’après cette recherche, des travaux ont été plus réalisés dans les pays à hauts revenus comme le Canada, les Etats Unis et le Royaume Unis que dans les pays à revenus intermédiaires et faibles. Le cadre d’analyse théorique a été inspiré de l’approche d’analyse de la perception de Ban et al. (1994), du modèle Transactionnel Stress-Coping de Lazarus et Folkman (1984) et l’approche des Moyens d’Existences Durables du Département du Développement International (1999). La démarche méthodologique utilisée pour ce travail reste théorique et ne peut être infirmée ou confirmée que par des enquêtes de terrain.Farmers' mental health is a determining factor in adaptation to the effects of climate change. This article summarizes the existing literature on mental health, the factors associated with it and the adaptation of populations to the effects of rainfall variability. It aims to analyze mental health and its determinants, which may influence producers' adaptation to climatic shocks. This work was conducted through a literature search using search engines such as scopus, Google Scholar, Refseek, BASE and Pubmed. A series of scientific documents dealing with various themes related to the subject was selected and subjected to careful reading and analysis, using the PRISMA method, to identify relevant documents. Theoretical approaches were also researched, enabling the construction of a theoretical analysis framework that could describe farmers' adaptation strategies in a changing climate context. According to this research, more work has been done in high-income countries such as Canada, the United States, and the United Kingdom than in middle- and low-income countries. The theoretical framework of analysis was inspired by Ban et al.'s (1994) perception analysis approach, Lazarus and Folkman's (1984) Transactional Stress-Coping model and the Sustainable Livelihoods approach of the Department for International Development (1999). The methodological approach used for this work remains theoretical and can only be confirmed or invalidated by field surveys.
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.
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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".