Consumer perceptions of insect consumption: a review of western research since 2015
Bibliographic record
Abstract
Summary Edible insects have been touted as a sustainable food of the future, but for Western consumers, the concept of entomophagy is largely unfamiliar and often disgusting. This review article discusses current trends in perceptual entomophagy research in Australia, Canada, Europe and the USA since 2015, along with an analysis of the guiding theoretical approaches to predicting insect consumption. Instead of trying to convince unwilling consumers, sensory and consumer science should turn to optimising insect‐eating experiences for potential early adopters. Hedonic evaluations of insect‐based products highlight differences in regional palates, but certain emotional responses seem consistent, including a group of newly coined ‘food‐evoked sensation seeking emotions’. Through clear‐cut insect‐inclusive legislation and effective product development, entomophagy‐specific fear and disgust may diminish over time. Researchers, food companies and governments all play critical roles in integrating insects into modern food systems, but consumer behaviour will ultimately determine the success of novel foods like insects.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".