Brown-out of policy ideas? A bibliometric review and computational text analysis of research on energy access
Bibliographic record
Abstract
Introduction The target of universal access to affordable, reliable, and modern energy services—key for individual, social, and economic well-being—is unlikely to be achieved by 2030 based on the current trend. Public policy will likely need to play a key role in accelerating progress in this regard. Although perspectives from the field of policy studies can support this effort, to what extent they have been employed in the literature on energy access remains unclear. Methods This study analyzed nearly 7,500 publications on energy access through a combination of bibliometric review and computational text analysis of their titles and abstracts to examine whether and how they have engaged with public policy perspectives, specifically, policy process research, policy design studies, and the literature on policy evaluation. Results We discovered 27 themes in the literature on energy access, but public policy was not among them. Subsequently, we identified 23 themes in a new analysis of the 1,751 publications in our original dataset, mentioning “policy” in their title or abstract. However, few of them engaged with public policy, and even those that did comprised a rather small share of the literature. Finally, we extracted phrases pertaining to public policy in this reduced dataset, but found limited mention of terms related to the policy process, policy design, or policy evaluation. Discussion While to some extent this might reflect the multidisciplinary nature of the research on energy access, a manual review of the abstracts of select publications corroborated this finding. Also, it shed light on how the literature has engaged with public policy and helped identify opportunities for broadening and deepening policy relevant research on energy access. We conclude that, despite their relevance to energy access, public policy perspectives have infrequently and unevenly informed existing research on the topic, and call on scholars in both communities to address this gap in the future.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | Bibliometrics Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.078 | 0.177 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".