Renewable Energy Powered Rural Community Development Centres in the Developing Countries
Bibliographic record
Abstract
People in the developing countries who lack basic services and economic opportunities are primarily concerned with improving their living conditions. At present, unemployment problem in the rural areas of the developing countries are diversifying the moral values and social responsibilities of unemployed youth. To solve the problem, rural development centres (involving vocational training, IT services and other productive activities) can contribute significantly for the upliftment of these rural youths and can transform them into grass-root entrepreneurs. One critical factor hindering the establishment of such rural development centers is access to affordable and reliable energy services. Under this backdrop, environmentally benign renewable energy systems can contribute significantly in providing much needed energy in the unserved or underserved rural development centers in the developing countries to achieve both local and global environmental benefits. The paper demonstrates that energy deficient, economically backward communities in the off-grid areas of the developing countries, can be given an array of opportunities for income generation and social progress through rural development centers with the aid of renewable energy sources (such as wind, solar photovoltaics, solar thermal, biomass and micro-hydro), thereby improving their standard of living. Poverty alleviation in rural areas can be accomplished and the critical role of access to adequate level of energy services, Information Technology (IT) and modern communication facilities in it demonstrated. Furthermore, the production, implementation, operation and maintenance of renewable energy applications being labor-intensive, will also result in job growth in the village context, preventing migration of labor force, especially of young men, from rural areas to overcrowded industrial areas. An appropriately designed renewable energy systems can also have a significant role in reducing the impact of climate change through non production of green house gases.
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 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) | 0.001 | 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 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".