Eating practice models in Spain and the United Kingdom: A comparative time-use analysis
Bibliographic record
Abstract
The time dedicated to eating is changing. Although a tendency towards the homogenization of eating habits has been confirmed, the scarcity of comparative studies means that it is impossible to know whether the variations are occurring equally or with the same intensity in all countries. In this study, time dedicated to eating and cooking in Spain and the United Kingdom is analysed. Questions are asked regarding the decline in eating at home and the fragmentation of meals. An analysis is made whether different social groups behave in a similar way with regard to the time spent eating and to what extent the changes affect some groups more than others, generating greater social differences. In order to do this, official Spanish and British time-use surveys are used, and the data from two different time periods are analysed using multivariate techniques. In both countries, signs of convergence are detected, although the speed of change is different. Despite the convergence, the results also show that the changes in eating habits are not linear and are affected by moments of intense social transformation. Phenomena such as the economic crisis in the case of Spain affect the society and impose specific eating habit trends, generating new forms of social differentiation.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".