Planning for a sustainable food system in the Alberta capital region
Bibliographic record
Abstract
Food is an essential substance for all life and a large component of our health and wellbeing,yet current priorities in the conventional food system suggest otherwise. Withinthe last decade, municipal and regional governments have taken on a larger role inaddressing questions regarding what we eat and where our food comes from. Similarly,it is only recent that planners have taken interest in addressing problems in the foodsystem. This Supervised Research Project explores, primarily through interviews, theopportunities and challenges for food planning and policy in the Alberta Capital Region.Findings indicate that a number of possible actions can be taken to protect farmland,resolve land use conflicts, invest in food infrastructure, and provide farmers and thegeneral public resources and information pertaining to educational, social and publichealth programs related to food. However, changes to the region’s governance structure,including the transfer of planning authority from provincial jurisdiction to the regionand sustainable funding mechanisms for the Capital Region Board, will be necessary toensure that the region has sufficient capacity and ability to support such initiatives. Forthe time being, planners must be proactive in protecting agricultural lands whendetermining areas for development. The immediate creation of a regional food policycouncil is also recommended to generate further discussion and initiatives amongstakeholders. Lastly, the economic dimension should not be overlooked in the planningof permanent agriculture zones. It is necessary to further examine the roles andresponsibilities of planners in food planning and policy. This examination will helpdetermine an appropriate framework to improve the food system in concert with otheractors.
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 | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".