Bibliographic record
Abstract
Newfoundland and Labrador faces considerable challenges in maintaining a consistent and reliable food supply. The lack of locally produced food has resulted in the province’s dependency on imported foods. Transporting this food to the province’s communities relies on the ferry service, which is sensitive to disruption, and thereby contributes to the province’s overall level of food insecurity. By increasing agricultural capacity, the province will be able to create employment, sustain rural economies, and increase local food production – all of which will help create a more food secure Newfoundland and Labrador. The barriers to increasing agricultural capacity in this province include a lack of infrastructure to promote and support labour and skill development; current policies and programs favour large-scale agriculture, and fail to meet the needs of the developing smaller-scale industries that are commonly found in rural areas. The establishment of cooperatives that help small-scale producers share services, such as egg grading and meat inspection, are essential to the development of competitive food production in the province. It is important that government support the creation of a service that will help farmers and entrepreneurs with marketing and delivery of their product. Increasing agricultural capacity in this province is essential to enabling the people of Newfoundland and Labrador to be self-reliant and food secure. Food security has been shown to be an important part of community health and integral to the prevention and control of many diet-related chronic diseases. Before rural populations further decline due to lack of economic opportunity, it is important that the provincial government seize the growing interest in and demand for locally produced foods and invest in smaller-scale local agriculture.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.038 | 0.004 |
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".