Harnessing the sun – addressing sociotechnical barriers to off-grid solar power deployment in Mozambique
Bibliographic record
Abstract
Mozambique has substantial solar power potential (23,000GWe) yet only 83MWe of installed capacity (representing 2% of the total 3623MWe generation capacity). Meanwhile, 44% of the population has electricity access, making Mozambique one of the least-electrified countries. Efforts to scale-up off-grid solar photovoltaics and improve rural electrification face key sociotechnical challenges. Using interview data from 33 national stakeholders, we identify the key policy, inter-agency coordination, socio-cultural development, and institution-driven actions needed to overcome these challenges. We introduce the concept of a ‘social multiplier effect’ to explain how small-scale electricity access improvements increase public demand for grid-based electrification, demonstrating how this can drive socioeconomic benefits to rural and peri-urban areas. We call for coordinated actions from policy and market actors, advocating for policy coherence and increased private sector involvement to boost investment, regulation and innovation in off-grid solar technologies, ultimately achieving universal electricity access and improving social development outcomes in Mozambique.
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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 | 0.001 | 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 | 0.000 | 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".