Maple Syrup Value Systems and Value Chains - Considering Aboriginal and Non-Aboriginal Perspectives
Bibliographic record
Abstract
Harvested from both intensive sugar maple stands and diverse mixed forest ecosystems across Ontario, maple syrup is an important rural and Aboriginal non-timber forest product that contributes to social, economic and environmental sustainability. This paper presents our ongoing work to map Ontario’s maple syrup value system from two different perspectives, Aboriginal and non-Aboriginal. In the economic sense, analyses of value systems are useful for members to identify the opportunities and challenges they are facing to advance industry growth and innovation. In the social and environmental sense, these analyses provide a window into how different worldviews and belief systems can lead to more effective and sustainable maple production. A value system is the inter-connected network of firms and activities that comprise an industry from the supplier to the consumer that is focused on quality and efficiency rather than costs. In this project, we pushed the boundaries of the traditional business approach, to incorporate sustainable development thinking and re-imagine the mapping according to Aboriginal ways of knowing. We undertook thirty four interviews representing Aboriginal and rural industry members and other key informants. We compare and contrast the rural and Aboriginal models of the value systems and conclude by providing insights useful for community forestry operations.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".