Influence of Accessibility to the Infrastructure and Natural Resources on Lifestyle and Workload of Rural Women: Scenario of Indian Central Himalaya
Bibliographic record
Abstract
The women of rural central Himalaya are considered to be the backbone of village economy, as traditionally, they put more than 15 hours a day in various activities in this region. The present study deals with analysis of the workload on women, (in terms of energy expenditure), in three major sectors (household, animal care and agriculture) in six representative/sampled villages at different altitudes/locations in Bageshwar district of Uttarakhand, with respect to accessibility to the infrastructure, availability of the natural resources, traditional division of labour and cultural setting. Based on the results of earlier studies, two age classes of women (15-35 and 36-55 years) were considered for the present study because of their maximum (>80%) contribution on performing these three major activities in this region. The results of the present study clearly indicate that the residents of mid elevations having comparatively poor accessibility to the infrastructure and moderate availability of the natural resources are struggling hard for the subsistence and putting maximum on agriculture related activities whereas, the women from lower and the higher elevation are putting minimum on agriculture. Accessibility to basic amenities and infrastructure have largely impacted on the division of labour among the women as younger women are engaged on house hold and animal care and the elderly women put more on agriculture at Naughar and Nakuri, whereas trend is more or less reverse at remote villages. Improved accessibility to the basic amenities, low cost technological inputs and conservation of natural resources could reduce the work load and improve livelihood of the residents.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".