Fisheries Centre research reports. Volume 30, number 1
Bibliographic record
Abstract
Colonial development has severely altered landscapes throughout Canada, including in Tsleil-Waututh Nation’s (TWN) territory, centred on present-day Burrard Inlet, BC, where urban and industrial expansion has modified the inlet’s shoreline for well over a century. These shoreline changes have degraded the ecosystem and affect TWN in innumerable ways, but non-Indigenous communities have not considered the impacts of total shoreline change in detail, and generally accept shoreline changes that have occurred since European contact as the “baseline” condition of Burrard Inlet. In this study, we therefore used multiple lines of evidence to reconstruct the shoreline of Burrard Inlet as it existed prior to European contact in 1792 and quantified the spatial extent of intertidal and subtidal area change in the inlet from 1792 to 2020. The results demonstrate that, across Burrard Inlet, a total of 1,214 ha of intertidal and subtidal areas have been lost to development and change, including 55% (945 ha) of the inlet’s intertidal areas. The most severe shoreline alteration occurred in False Creek and the Inner Harbour, including loss and elimination of ecologically productive and culturally important intertidal habitats at False Creek Flats (>99% intertidal area lost), the Capilano River Estuary (80% intertidal area lost), and the Seymour-Lynn Estuary (56% intertidal area lost). This shoreline loss has fundamental consequences to Burrard Inlet’s ecosystem and TWN’s ability to exercise constitutionally-protected rights. Further, this work demonstrates that any potential future shoreline loss must consider historical shoreline change and cumulative effects in Burrard Inlet.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.529 | 0.362 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".