Bibliographic record
Abstract
"There are efforts by a variety of social movements and civil society organizations\nto encourage the development of alternative agri-food networks that are socially just,\necological, humane and which ensure food security and food sovereignty. Many activists\nfocus their critiques on the role of large multinational corporations in restructuring and\nglobalizing the agri-food system. They offer in its place a vision of locally oriented,\nsmall scale ecological farming. Drawing on the gendered experience of small scale\nwomen farmers on Vancouver Island, BC, Canada who are developing local markets for\ntheir farm products and the impact of new Provincial food safety regulations, this paper\nargues if such social change initiatives are to be successful, one will need to look at how\nfood safety regulations accomplish outcomes that have relatively little to do with food\nsafety but effectively close the possibilities for more ecologically grounded and locally\nfocused food production and distribution. That is, food safety regulations seem inevitably\nto close off to farmers the possibility of economic alternatives to the globalizing agri food\nsystem. There will be 'no alternatives'. Paradoxically, consumer led food and food\nsecurity movements can undermine the very changes they wish to see happen." (author's abstract)
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.016 | 0.010 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 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; 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".