MétaCan
Menu
Back to cohort
Record W7135557882

Food Waste and the Shopping and Consumer Behaviour of Czech Households – June/July 2023

2023· report· cs· W7135557882 on OpenAlexaboutno aff
Naděžda Čadová

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2023
Typereport
Languagecs
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCzechFood wasteQuarter (Canadian coin)Public opinionConsumer behaviourGreen foodQuestionnaireFood products
DOInot available

Abstract

fetched live from OpenAlex

In its regular survey the Public Opinion Research Centre at the Institute of Sociology, Czech Academy of Sciences, examined the Czech public’s attitudes and opinions on the issue of food waste. More than a half (52%) of the respondents consider food waste to be a big problem, more than two-fifths (42%) think food waste is not right, but there are more urgent problems that need to be solved and only twentieth (5%) of the Czech public does not consider food waste to be a big problem in society.\n\nThe most important reason for reducing food waste according to respondents is to save money for their household (75%), while the least important reason is to change society through their behavior (34%).\nThe majority (55%) of respondents go shopping several times a week, while a quarter (25%) go shopping once a week. 14% of respondents shop every day.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.167

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.030
GPT teacher head0.269
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueDigital Repository (National Repository of Grey Literature)French-language works237,207