Why in my backyard (WIMBY): Forging the link to community futures when energy transition projects are met with indifference
Bibliographic record
Abstract
This paper analytically works towards foregrounding a new concept which can be useful to describe local reception and perceptions related to energy transition projects: Why in my backyard (WIMBY). We define this concept as local indifference to take part in changes in local energy landscapes at the community level. Based on the reception and data from two pilot and demonstration projects in Arctic Norway we show how locals passively accept, or reluctantly support green measures taken in fisheries (Lofoten) and energy systems (Senja). We suggest that these findings might be a symptom of a problem across sites: Even if local publics are in favor of green transitions and recognize the challenges of climate change, they don't necessarily see the relevance to their community. This has several implications besides potential foot-dragging, as pilot and demonstration projects struggle to anchor socio-technical measures in communities. On one hand, we suggest that if a project overlooks local community practices or does not adequately engage with the concerns of the local community, ‘Why in my backyard’ (WIMBY) can easily turn into ‘Not in my backyard’ (NIMBY). On the other hand, we suggest that a way forward is to consider stakeholders or involve local communities in solutions when developing new energy landscapes by focusing on how community futures can be sustained and potentially improved by being pilots of change. Building on our data by tying the spatial and material conditions to practices of change, we draw lessons from practices at a community level and show the potential uneven outcomes that socio-technical experimentation entails, drawing on interviews and participant observation in Lofoten and Senja. The paper concludes by reflecting on the theoretical implications of WIMBY and offers some suggestions for enhancing community engagement.
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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 | 0.013 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.024 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".