Killing with Kindness: is whale watching in the Salish Sea killing the Southern Resident Killer Whales? : how the social representation of the endangered Southern Resident Killer Whales has a big incentive on locals’ actions to protect the pods
Bibliographic record
Abstract
The fish-eating Southern Resident Killer Whales (SRKW) live in the Salish Sea and have been listed as endangered by the U.S and Canada in early 2000s. Their population is still declining with only 72 individuals left in May 2020. Reasons for their endangerment go from toxins in the water to underwater disturbance and lack of prey, although the latter is favourited by scientists. The whale watch industry is being blamed by many because of the number of whale watching boats on the water and their physical proximity of the SRKW. \n \nThis thesis is focusing on the inhabitants of the Salish Sea and their perception of the SRKW and the whale watch industry and how they are making sense of the situation. Through the use of the Social Representations’ theoretical framework, it is shown that mechanisms such as stories, anthropomorphization, scapegoating and psychological ownership are used by the interviewees to strengthen their social representation of the SRKW but also to take decisions or actions for the pods’ survival. The conclusion of this paper summarizes that the whale watch industry is unfairly scapegoated for its activity as it is not the only actor responsible for the SRKW’s endangerment and disappearance from the Salish Sea. Even more, the whale watch industry is one of the only actors involved in the pods’ survival to have made changes in its practice by creating voluntary guidelines which limit the speed and distance a boat can get around the SRKW. In order to save the endangered SRKW from extinction, most interviewees agree that the priority should be put on solutions to bring the pods’ favourite prey, the Chinook salmon, back in the Salish Sea.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".