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Record W4395071665 · doi:10.3390/foods13091309

Consumer Perceptions of the Canadian Salmon Sector and Their Associations with Behaviors: A Perspective from Indigenous Rights

2024· article· en· W4395071665 on OpenAlexaffabout
Sylvain Charlebois, Ning Sun, Ken Paul, Isaiah Robinson, Stefanie M. Colombo, Janet Music, Swati Saxena, Keshava Pallavi Gone, Janèle Vézeau

Bibliographic record

VenueFoods · 2024
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of TorontoAssembly of First NationsDalhousie University
Fundersnot available
KeywordsIndigenousSustainabilityPerceptionMarketingPurchasingConsumer behaviourInclusion (mineral)RealmBusinessPublic economicsPublic relationsPolitical scienceEconomicsPsychologySocial psychology

Abstract

fetched live from OpenAlex

Previous studies on consumer perceptions and behaviors of salmon have often neglected Indigenous rights within the Canadian salmon sector. This study innovatively addresses this gap by integrating Indigenous rights into the current analysis, alongside considerations of sustainability practices, socio-economic impacts, and consumer motivations. Our research objectives aim to fit three consumer perceptions-environmental sustainability, economic considerations, and Indigenous rights-and to evaluate their associations, alongside perception of a price increase, socio-demographics, and consumer motivation factors, with purchasing behaviors related to Canadian salmon products. Data for this study was collected from a nationwide online survey. Responses to Question 2 and Question 35 are encoded with numerical values ranging from 1 to 5, where larger numbers indicate stronger agreement with the statement. The inclusion of methodologies such as the Graded Response Model (GRM) and Cumulative Link Models (CLM) adds another innovative dimension to this study. Our findings demonstrate how consumer profiles are associated with these four perceptions and their underlying determinants. Furthermore, the study quantifies the influence of these four perceptions on each consumer purchase behavior. The implications of these findings extend to the realm of mathematical modeling in consumer decision-making processes, offering practical insights for businesses and marketers, and emphasizing the importance of implementing regulatory frameworks and initiatives that promote sustainability, safeguard Indigenous rights, and address socio-economic disparities.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.550
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.329
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes2
Has abstractyes

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