Burning dung cake as a household fuel: A review
Bibliographic record
Abstract
Millions of households in developing countries burn dung cakes made from common farmyard manure to fulfil their household energy needs. Localised studies investigate dung cake use and its impact. However, a comprehensive review of the social practice of dung cake use as a household fuel and its impact are not available. Our exploratory systematic review on the social practice of burning dung as fuel and its impacts, reveals that due to their higher emissions than fuelwood and crop residue, dung cakes are primarily situated at the bottom of the energy ladder and are used as a niche fuel by energy-poor households. This review underscores the notable absence of knowledge about the social practice of dung cake as a fuel. Our study on the practice of burning dung cake as household fuel, dung cake users, their communities, and the context they are using dung cake helps to identify policy strategies as part of the clean energy transition, to benefit communities and improve global clean cooking practices. We highlight the importance of identifying cost-effective behavioural changes and context-specific solutions to accelerate the clean cooking transition in these communities.
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 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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".