Perceptions of plant‐based fish among Atlantic Canadians
Bibliographic record
Abstract
There is an increasing demand for plant-based alternatives by individuals living in the Western world. One of the newer plant-based alternatives is plant-based fish and seafood (PBFs). This study aimed to investigate individuals' opinions and attitudes toward PBFs, as well as evaluate the effect of involvement in the fishing industry on the participants' attitudes. Participants (n = 183) were asked to answer questions about their perceptions of PBFs. Participants believed that PBFs were environment-friendly and were interested in trying PBFs but were concerned about the taste and texture of PBFs. Although participants were likely to try PBFs, they were less likely to add them to their regular diet. After reading messages about the benefits of PBFs in this study, participants' willingness to try PBFs and add PBFs into their regular diet increased. In addition, those who worked in the fishing industry or had high food neophobic scores did not believe that PBFs would taste like conventional fish and seafood products. Future studies should investigate the attitudes of individuals living in different regions and investigate whether exposure to PBFs affects consumer perceptions of the food product. PRACTICAL APPLICATION: Consumer demand for new plant-based products is increasing, but before new products can be released, participants' attitudes and perceptions need to be evaluated. Plant-based alternatives to fish and seafood are a new food product, and therefore, participants' attitudes toward them need to be investigated. It was found that the individuals were more willing to try plant-based fish and seafood. In addition, they were more likely to incorporate them into their diet after reading about the nutritional benefits and sustainability of PBFs.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".