Views from the shore: An analysis of public comments on an offshore wind energy future in Nova Scotia, Canada
Bibliographic record
Abstract
Centered around concerns of climate change, energy security, and the need for low-cost clean electricity, many jurisdictions that have access to maritime areas are developing offshore wind energy. The province of Nova Scotia, Canada – home to some of the strongest offshore wind resources in the world – is one such place. Yet before development, governments need to listen, understand, and respond to the views of a diverse set of stakeholders, and affected publics. Using online and in-person open house comments, this exploratory study was conducted to determine the level and type of socio-political acceptance during the initial planning stages of offshore wind energy in Nova Scotia. Content analysis revealed that many people who participated in these consultations were initially ambivalent/unclear (with more opposed than supportive) – with regard to offshore wind energy. Consultees most opposed were Indigenous peoples/representatives, members of the general public, and Non-Government Organizations (NGOs). Thematic analysis identified six main themes, with the most referenced being concerns around biodiversity impacts and general environmental concerns. We close the paper with a discussion of the broader implications of our work, including relevance to future research, planning, and policy.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.014 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".