Controlled environment agriculture and containerized food production in northern North America
Bibliographic record
Abstract
There is an ongoing debate about the role of controlled environment agriculture and containerized food production in local food systems in Northern North American communities. Some critics dismiss these applications as ineffective, arguing that because they marginalize certain populations they do not have a place in northern food systems. However, such critiques are premature and undermine what may prove to be an important and complementary component of local and regional food systems in the north, particularly if designed and implemented in a culturally appropriate and place-based context. Containerized food production can offer enhanced food production capabilities for communities through year-round production. While there are still concerns about proper growing protocols, scalability, output, durability, and economics, these can be addressed, modified and improved through research and continued applications. New opportunities requiring further exploration in the application of containerized food production systems include, but are not limited to, integrative systems design, the enhancement of community development initiatives, and the integration of the social networks that are necessary for diversified local food production.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".