Bibliographic record
Abstract
A significant part of the regular CVVM Our Society survey conducted in June and July 2023 was dedicated to the topic of homesteading and gardening.\n\nThese topics are part of the activities of the Institute of Sociology of the CAS within the framework of the AV21 Food for the Future Strategy.\n\nSpecifically, we investigated whether people engage in various activities related to subsistence farming, whether they produce their own food (fruits, vegetables, eggs, meat, etc.) and if so, where and why, whether people who grow or produce something in their households give these products to someone or exchange them with someone, or with how many people.\n\nWe were also interested in the other side of the story, i.e. whether people themselves receive home-grown or home-produced food from someone.\n\nLast but not least, we also looked at how bio-waste is managed and how the current food supply compares to ten years ago.\n\nAbout half (47%) of people grow their own food in their garden, 7% in their flat or on their balcony.\n\n\nThe most important reasons why people produce their own food are obtaining healthy food (25%), fresh food (24%), saving money (19%) and that it's a hobby (15%).\n\n\nMore than two thirds (69%) of people give or trade some of what they grow or produce in their household to someone.\nPeople are most likely to receive home-grown food from close family members (55%) and friends (50%).\n\n\nThe most common way of managing bio-waste is to use brown bins (57%), and almost half of people compost bio-waste in the garden (47%). Around a quarter of people who sort bio-waste in their household take it to a collection yard (26%) or give the sorted bio-waste to animals (25%). Less than a fifth use bulk containers (18%) or donate it to someone else (17%). The use of vermicomposters (5%) and community gardens (1%) is very marginal.\n\n\nHalf (49%) of people work in their garden on a regular basis, i.e. at least once a month during the season, a third (33%) go foraging for mushrooms, berries or herbs, and 12% keep domestic animals.\n\n\nMore than two-fifths (41%) of respondents believe that their household food supply has not changed between now and ten years ago.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.042 | 0.005 |
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".