Is anti-consumption driving meat consumption changes in Australia?
Bibliographic record
Abstract
Purpose The purpose of this paper is to evaluate recent changes made by Australian consumers in their consumption of beef, chicken, pork and lamb, as well as the factors motivating both decreased and increased consumption of each type of meat. Reasons for meat-avoidance are also examined. Design/methodology/approach An online questionnaire was completed in July 2016 by two Australian samples comprising: adults from the general population; and vegetarians. Data were analysed for 287 meat consumers and 82 meat avoiders. Descriptive statistics and results of multinomial logistic regression models are presented. Findings Meat consumers most commonly reported reducing consumption of beef in the last 12 months (30 per cent); followed by lamb (22 per cent), pork (14 per cent) and chicken (8 per cent). The following factors were associated with reductions in meat consumption: concerns regarding price and personal health; age and household income; and food choice motivations related to personal benefits, social factors and food production and origin. Main reasons motivating meat-avoidance were concerns regarding animal welfare, health and environmental protection. Originality/value This is the first Australian study providing national-level insight on how and why meat consumption patterns are changing. Reasons for changes are examined through an anti-consumption lens, investigating rationale for avoiding, reducing and increasing consumption. This provides a more comprehensive understanding of meat consumption and anti-consumption decisions, which are becoming increasingly complex. Insights on the psychologically distinct motivations underpinning avoidance, reductions and increases in meat consumption can inform the development of strategies aimed at promoting a societal-shift towards consumption of more sustainable dietary protein sources.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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; both teacher heads agree on what is shown here.
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".