Mixed cropping systems of Adivasi peoples in India using the domain analysis participatory technique
Notice bibliographique
Résumé
Introduction Since the early 1990s, small grassroots development organizations have achieved notable successes with participatory research and development. As a result, national and even multilateral organizations have faced increasing pressure to also adopt participatory ideas and techniques. Now virtually all development organizations demand local participation on some level in at least some part of their project implementation. The benefits of participatory research and development systems such as Participatory Rural Appraisal (PRA) are well documented and supported (see for example Pratt 2001; Opp 1998; Whyte 1991). In brief, the research techniques are interactive, visual and tactile, so that anyone can participate regardless of age, social status or level of education. Secondly, participating people maintain ownership of their knowledge and of development processes. Furthermore, they are encouraged to use their knowledge to serve their own development needs rather than having an outside party decide what is good for them. The sense of ownership feeds into a third benefit, which is that “participation” is empowering for local people because they are looked upon as the experts harbouring valuable knowledge. In general, the results are that development projects are more appropriate in both scale and substance. Therefore, they are also more successful because they actually reflect the needs and wants of the stakeholders who are most impacted. However, as participatory systems are increasingly applied on a larger and larger scale, they are criticized for often falling short of meeting their ideal goals. The above mentioned benefits are only benefits if “participation” is enlisted from local people with the best intentions, behaviours and attitudes (Opp 1998). Critics are arguing that knowledge elicited using participatory methods are at best superficial due to rigid applications of techniques stripped of their theoretical underpinnings, a lack of investment in time, money and rigorous preliminary social research, and the alienation of knowledge from participants as it is taken to outsider “experts” for analysis. As a result, participants do not actually receive any benefit to participating, leading them to offer little support and even resisting research and development proposals. In other words, research and development projects are not achieving their potential for success (Chevalier and Buckles 2005; 2005b; Kapoor 2002; Li 2002; Campbell 2001; Pratt 2001; Gomez 1999; Sillitoe 1998; Opp 1998; Mosse 1998; 1994). Given the growing body of literature criticizing PRA and other existing systems of participatory research, Drs. Jacques Chevalier and Daniel Buckles developed the Social Analysis System (SAS) with funding from International Development Research Centre (IDRC) in Ottawa, Canada. SAS builds on the established legacies of its
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 | 0,029 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| 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 ».