Consumers on a Mission to Force a Change in Public Policy: A Qualitative Study of the Ongoing Canadian Seafood Boycott<sup>1</sup>
Bibliographic record
Abstract
ABSTRACT Netnography (i.e., the online equivalent of ethnography) was used to analyze consumer boycott pledges submitted to an online boycott petition that was designed to recruit consumer participation in the contentious Canadian Seafood Boycott. The purpose was to investigate what motivates consumers to pledge boycott participation as well as to provide a preliminary understanding of boycott pledgees' psychographic makeup. The findings show that petition signatories are generally very angry about the Canadian Seal Hunt, pledge to boycott for a variety of objectives (instrumental, expressive, and punitive), abhor cruelty against animals, do not believe that it is acceptable to kill an animal for its fur, and worry about the environment in general. Many are very religious and quite a number believe that traditions that embrace animal cruelty need to be abolished. The findings further indicate that concern for animal welfare/rights has been moved into the mainstream.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".