Bibliographic record
Abstract
The purpose of the research is to improve our understanding of the adaptation process in agriculture at the farm level and the influence through the value chain. The research identified critical managerial decision areas in the strategic planning process of blackcurrant growers in Alberta and the South Island of New Zealand. The work was a comparative study of growers that attempted to determine the correspondence between the results of case study observations and a set of theoretical propositions that were developed from a review of the relevant literature. Results indicate that growers understand their own firm’s core competencies, plan strategically and contingently to maintain flexibility and retain niche advantages. Data gathered on the blackcurrant sectors in Canada and New Zealand provided the contextual basis for the selection and analysis of the grower case studies. The sector analysis reached across the value chain. Among the findings reported was the interesting observation that although niche marketing is an accepted strategy in the marketing literature as a means to adaptive change, and although the flexibility inherent in this approach is critical to the success of traditionally resource-starved small firms, it is not clear that the firms reported on in this study engaged in niche marketing as a planned strategy but rather came upon the opportunity through serendipity. In terms of country comparison, results indicate that there may be some specific factors that contribute to the success of the blackcurrant industry in New Zealand. Closer examination of these factors may be beneficial to assisting the Canadian sector. Keywords: Niche marketing, strategic planning, adaptation flexibility JEL Codes: D81, L1, M31, O13, Q13
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".