Developing a Framework for Rural Electrification in India- Analysis of the Prospects of Micro-grid Solutions
Bibliographic record
Abstract
The present research examines the perceptions of rural consumers towards the microgrid and rural electrification (RE) based solutions and develops a framework for improving the establishment of rural RE based microgrid solution captured from a case study in the Kalimpong district of North Bengal. The study adopted a mixed methodology study design includes the qualitative and quantitative aspects of the study through stakeholder interviews and questionnaire-based primary survey of the sample households. The perceptions received from sample households were validated with the response from other stakeholders, including academicians, researchers and sectoral experts. Data were analysed using structural equation modelling (SEM). The findings of the present research indicate that to accelerate the socio-economic development of the hilly terrains of North Bengal region, multi-provider licensed based microgrid preferably with renewable-based is a preferred mode which ensures reliable and affordable access of electricity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".