Assessment of Circumpolar Agriculture in Canada through an Innovation Systems Approach
Bibliographic record
Abstract
Circumpolar agriculture is technically feasible and has the potential to improve food sovereignty in many communities of circumpolar Canada. This research project elaborated on the agricultural history of the circumpolar subregions (Yukon, the Northwest Territories, Nunavut, Nunavik and Nunatsiavut) and assessed the current state of circumpolar agriculture. Through the rapid appraisal of agricultural innovation systems (RAAIS) approach, this project also identified the constraints to agricultural development and provided specific entry points for innovation in the circumpolar agricultural system. Stakeholder analysis was used to identify potential study participants and demonstrated that there were a limited number of powerful stakeholders in the circumpolar agricultural system, making it difficult for stakeholders to have their concerns heard and addressed. Analysis of semi-structured interviews identified 24 constraints to agricultural development across the entire study region although their relevance varied between subregions. Secondary data collection corroborated interview data but was limited by the lack of publications pertaining to the subject. In all subregions, economic constraints were the main hindrance to agricultural development and encompassed a lack of human capital, limited capital cost recovery, logistical barriers and high operating costs. The agricultural innovation support system was restricted by the available infrastructure and assets, institutions, capabilities and resources. Agricultural development in circumpolar Canada could be facilitated by developing strategies which strengthen these structural conditions for innovation and increase the stakeholders’ capacity to address constraints to agricultural development. Possible strategies include the establishment of certified postharvest processing facilities, increased access to loans and funding, development of agricultural training programs and local warehousing options for agricultural inputs. With constraints having been identified during this study, further research could elucidate the extent of these constraints through survey administration. This would allow stakeholders to prioritize constraints and develop specific strategies accordingly
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".