Bibliographic record
Abstract
‘Local food systems’ movements, practices, and writings pose increasingly visible structures of resistance and counter-pressure to conventional globalizing food systems. The place of food seems to be the quiet centre of the discourses emerging with these movements. The purpose of this paper is to identify issues of ‘place’, which are variously described as the ‘local’and ‘community’ in the local food systems literature, and to do so in conjunction with the geographic discussion focused on questions and meanings around these spatial concepts. I see raising the profile of questions, complexity and potential of these concepts as an important role and challenge for the scholar-advocate in the realm of local food systems, and for geographers sorting through them. Both literatures benefit from such a foray. The paper concludes, following a ‘cautiously normative’ tone, that there is strong argument for emplacing our food systems, while simultaneously calling for careful circumspection and greater clarity regarding how we delineate and understand the ‘local’. Being conscious of the constructed nature of the ‘local’, ‘community’ and ‘place’ means seeing the importance of local social, cultural and ecological particularity in our everyday worlds, while also recognizing that we are reflexively and dialectially tied to many and diverse locals around the world.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.004 | 0.020 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".