Hybrid entrepreneurship in just transitions: Dealing with dilemmas facing ‘the other’
Bibliographic record
Abstract
• Hybrid ventures provide alternative value creation in just transitions for ‘the other’. • Hybrid entrepreneurship enables transitions on communities’ own terms. • Community identity and community embeddedness are essential to alternative value creation. • Spiritual, confessional and cultural values are key leverages for alternative value creation. The aim of the paper is to investigate the role of hybrid entrepreneurship in developing justice and diversity responses to sustainability transitions that are complicated by contexts of ambiguous socio-technological shifts and manifested in material and ethical dilemmas for ‘the other’, i.e., those deemed different. Based on analysis of two original case studies featuring the other—the Nisichawayasihk Cree Nation indigenous community in Canada and the Karachi Down Syndrome Program in Pakistan—we identify the conditions for engaging minority communities in strong collaborative and participatory cross-stakeholder processes to deal with dilemmas posed by sustainability transitions. We centre on issues of social inclusion and social equity. We illuminate how hybrid entrepreneurship practices enable, structure and manage collective learning within and outside hybrid ventures to facilitate equitable transitions. Finally, we propose how to co-create actions that amplify marginalized voices to influence institutions.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.032 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.001 | 0.020 |
| Research integrity | 0.003 | 0.003 |
| 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".