Bibliographic record
Abstract
Abstract This chapter brings the recent sociology of entrepreneurship, sociologies and geographies of responsibility, and critical reflections on place and space together to ask why entrepreneurs show leadership in a place, and where they might want to lead it. Drawing on a set of qualitative interviews conducted from 2018 to 2020 with small business operators in rural Nova Scotia, Canada, the chapter explores how interviewees frame their business ideas, decisions, practices and aspirations not (just) in terms of conventional business objectives like profit or market share, but in terms of something I term responsibility to place. Responsibility to place emerges through the interviews as a feeling that one’s business should make a positive impact on place – inclusive of its people, environment, culture, history, and future. This feeling exists in tension with the objectives of Nova Scotia’s entrepreneurial ecosystem managers, as is seen in the discrepancies between interviewees’ narratives and the discourses propagated by the province’s economic development agencies, focused as they are on export-led growth. The findings from this sample indicate that understanding the “geographies of responsibility” (Massey, 2004) in entrepreneurs’ narratives is critical to a fuller appreciation of entrepreneurial Place leadership.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".