Three sides to every story: Gender perspectives in energy transition pathways in Canada, Kenya and Spain
Bibliographic record
Abstract
Transitions toward a low-carbon future are not only technical and economical, but also deeply social and gendered. The gendered nature of energy transitions is often implicit and unexplored. As a corrective, this paper explores energy pathways by applying concepts from innovations and gender studies. We examine gender perspectives and niche energy innovations which could disrupt the regime. The regime represents the mainstream pathway that includes the dominant gender perspective and energy system. We explore different gender perspectives of energy transition pathways by applying an Alternative Pathways framework that includes: (1) on-stream pathways that exist within the mainstream pathway to promote equal opportunities for women and men, as well as niches for energy innovations without challenging the high-carbon energy regime; (2) off-stream pathways that depart from the mainstream and promote differences across different genders while creating niches outside the energy regime; and (3) transformative pathways that are fundamentally different from the previous mainstream and includes all gender perspectives in a new energy regime. Applying this framing, in Canada, we explored Indigenous perspectives in the oil sands sector; in Kenya, we studied largescale renewable energy impacting Indigneous communities; in Spain, we evaluate the movement away from fossil fuels and towards renewable technologies. The framework helped to identify that mainstream pathways represented the dominant male perspective while woman's perspective were largely left out. Such absence generate energy pathways that are disconnected from local realities, lack public buy-in and slow-down a sustainable energy transition.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.030 | 0.021 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".