Exploring the Opportunities and Constraints to the Success of Newfoundland's Wild Lowbush Blueberry (Vaccinium Angustifolium Aiton) Industry
Bibliographic record
Abstract
Newfoundland and Labrador’s biophysical environment has not been particularly conducive to crop agriculture. The province’s agricultural industry accounts for only 1% of its GDP. The number of farms, farm operators, farmland, and cropland within Newfoundland and Labrador are all experiencing decline outside of national averages. This has led to great provincial interest in increasing agricultural capacity in the province. A potential avenue for agricultural development is strengthening the province’s wild blueberry industry. Through a mixed methods case study that involved a geographic information system-based multi-criteria land suitability analysis and interviews, this research explores the potential for this industry and the different challenges and values that may impact it. This thesis analyzes the biophysical potential for this industry through the manipulation of various geospatial layers to determine suitability for commercial wild lowbush blueberry farming. This thesis also engages with perceptions of the barriers that impede the wild lowbush blueberry industry in Newfoundland as well as the potential opportunities to strengthen this sector. Finally, it examines the socio-cultural values surrounding wild lowbush blueberries in Newfoundland and cautions that these values may be more important than the potential market value created through blueberry commercialization
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".