The generational divide: How late entrant entrepreneurs influenced field frames in the Ontario wine field
Bibliographic record
Abstract
Although research has shown how entrants create markets, few studies have explored how late entrant entrepreneurs influence institutional change in already formed markets. Our study considers how varying late entrant subgroups shift market meanings reflected in field frames used by producers in the media in ways that spur field change. We do this within the context of the Ontario-grown wine category from 1985 to 2018. We show that later generations founded prior to or around the category’s legitimation influenced the salience of field frames that refined and incrementally changed the category. Later generations founded after legitimation and second-career lifestyle entrepreneurs influenced the salience of field frames that contended against regulations that benefited other categories but hindered the growth of their category. Concurrently, our insights help further understanding of how late entrants change an existing category to not only create a space for their distinctive identities but also enhance the viability of the category overall.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".