Salmon farm location in the Broughton Archipelago, British Columbia : a quantitative analysis
Bibliographic record
Abstract
The Broughton Archipelago on the northeast coast of Vancouver Island has the highest density of salmon aquaculture in the province of British Columbia, with 27 farms operating in an area of 117 km2. The Archipelago has been a focus region for early developments of spatial resource databases; it was the site selected for conducting the 1997 Salmon Aquaculture Review; and it has been the origin of recent controversies over the (mis)use of local ecological knowledge of First Nations and other interest groups. Many of the studies conducted in this area have focussed on the impacts of salmon farming on the local ecology. However, to date, little attention has been paid to what drives the industry at the regional level. By examining the distribution of salmon farms within the Archipelago and their spatial relationship to five different factors, this thesis aims to shed light on how and why the salmon aquaculture industry in the Broughton Archipelago has evolved over the last 20 years. This work examines the effectiveness of current siting guidelines in minimizing the impacts of salmon fanning and protecting the long-term sustainability of B.C.'s coastal ecology. Geographic Information Systems and spatial data analysis are used in combination to test the validity of five hypotheses on the potential drivers of the location of salmon farms in the Broughton Archipelago. Temporal analysis is used to compare the intended versus actual use of three spatial databases in shaping the development of the industry along the coast. Salmon farms in this region are found to be clustered by company, and located in areas of high biophysical capability where coastal resource interests and activities are also concentrated. These sites are not selected for their proximity to processing plants, hatchery facilities, or labour. Salmon farms, as currently distributed, are equally likely to be found in areas that meet the existing siting criteria as those that fail to do so. The findings of this research will be of fundamental importance as the province of B.C. faces the decision of whether to continue expanding the industry balancing risks with economic rewards, or to limit expansion until more is known about the costs and long-term impacts.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".