Agricultural training for Pakistan’s rural women
Notice bibliographique
Résumé
While women play an equally important role as men in Pakistan's farming systems, they typically have little access to information on modern farming techniques due to cultural rules that prevent them interacting with male agricultural extension staff.In 2013 and 2014, CABI initiated farmer training activities specifically targeting women in two areas of the country: Gilgit-Baltistan in the high north, and southern Punjab in the flatter central part of Pakistan.In the north, CABI worked with a local development project to set up farmer field schools for both men and women; these focused on production of tomatoes and dairy livestock.In southern Punjab, CABI's Skills for Farms project ran a series of three-month, village-based training courses in kitchen gardening and grain storage, targeting women between 16 and 35 years old.In each case, the training courses were designed to focus on household farming activities that are typically the responsibility of women.In Punjab, attitudes towards the training of women had become more positive following the floods of 2010, when numerous development organisations set up support programmes in the area to help communities restore their livelihoods.In Gilgit-Baltistan, there was much greater initial scepticism and criticism of women's involvement in the field schools.However, after the first batch of trainees was seen to make significant progress in their farming knowledge and practices, community attitudes to the programme were transformed.Women's influence and respect within their households also improved.Prior to the training, less than 5% of women interviewed in southern Punjab reported having a say in household spending decisions; that figure rose to almost 50% after the training.Beyond the household, trained women have also become more respected in their communities as a source of knowledge on modern agricultural practice.Importantly, impact research has also revealed different responses among women and men in adopting the new farming methods.In Gilgit-Baltistan, all women trainees were found to be earning more money from their tomato and dairy activities, which they had significantly increased following the training.Men, in contrast, were less interested in the production aspects of the training, which they tended to pass on to female household members, and were more interested in 'monetising' the training, through the marketing skills they were taught.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,046 | 0,006 |
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 source (Gemma direct ou Codex distillé), 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 ».