How Provincial and Local Discourses Aligned Against the Prospect of Dam Removal in New Brunswick, Canada
Bibliographic record
Abstract
In 2013, the state-owned electrical energy utility in New Brunswick, Canada, announced that a problem with concrete expansion was shortening by 40 years the expected life of the 660 MW Mactaquac Generating Station on the Saint John River. Its construction late in the 1960s, and the subsequent inundation of 10,000 hectares (ha) was part of a regional modernisation programme. Locals lost homes, agricultural land, communities and landmarks and a new mill changed livelihoods and attracted new people. In the intervening decades, the reservoir has become locally cherished for waterfront living and pleasure boat recreation. Since 2012, independent social science research about the fate of the dam and headpond has been undertaken in parallel with stakeholder engagement and public relations by the electricity utility. The final decision was delivered late 2016. The chosen option was to extend the dam’s life through repairs in situ, not one of the options formally under consideration. This paper presents provincial-scale discourses on the Mactaquac decision, using a 2014 energy survey of 500 New Brunswick residents which included questions about the Mactaquac decision. Analysis reveals how provincial preferences aligned with local qualitative research (summarised in an Appendix), revealing preferences for ongoing headpond amenity and the avoidance of further trauma associated with major landscape change. Preferences of First Nations to remove the dam may yet prove disruptive to the announced option. The discussion summarises aspects of the case study relevant to other instances of dam removal and landscape transition, as well as exploring options for further theoretical development, testing or application. These opportunities include: why males and females demonstrated different scales of concern around Mactaquac; the implications of different framings of hydroelectricity development (e.g. sacrificial landscape or local energy) on removal debates; and, how public decision-making can usefully engage with rather than dismiss uncertainty and path dependency.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 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, 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".