‘If I could afford an avocado every day’: Income differences and ethical food consumption in a world of abundance
Bibliographic record
Abstract
This study explores how ethical food consumption is framed in the accounts of ordinary people living in affluent societies, with a particular focus on income differences. Research on ethical consumption often associates ‘ethical’ with the consumption of certain predefined products. This study leaves the question of the content of ethical consumption open for empirical investigation. Further, instead of focusing only on the moment of purchasing, this study considers how people with different income levels relate to both food consumption and waste. The analysis draws from qualitative interviews with 60 people living in Canada and Finland. The analysis identified the techniques, subjects and norms through which the question ethical food consumption is posed by the informants and how they framed these issues with regard to income. The findings underline that ethical consumption is a socially constructed, contested and even internally contradictory discourse. Differences in income do not only mean differences in the role that money plays in food choices but also in what kind of consumption people consider worth pursuing. Further, differences in income dictate differences in how people are morally positioned vis-à-vis abundance. For people with a higher level of income, moral blame is asserted on wasteful consumption habits. For the people with a low income, in turn, it is ethically condemnable to refuse to rejoice at the abundance around us. The findings indicate that even in a society where the rhetoric of choice is prominent both as a right and as an obligation by which people ought to display ethical agency, the ethics of choice is tied to the resources available for consumption. People with a severely low income occasionally enjoy the trickling down of abundant treats and surprises. However, for them, occasional indulgence causes not only pleasure but also trouble.
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 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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.023 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".