Empowering Change: Innovations and Insights in Social and Emancipatory Entrepreneurship Research
Bibliographic record
Abstract
This Panel Symposium aims to explore the complex interplay of privilege and marginalization at societal and individual levels in the entrepreneurial landscape. Our focus encompasses adapting to evolving societal norms and expectations, as well as fostering equitable transitions in the face of various disruptions. Such disruptions may arise from shifts in social values and beliefs, the emergence of digital platforms, advancements in media technology, and instances of social unrest. The panel brings together entrepreneurship scholars to discuss issues and challenges related to research at the intersection of social and emancipatory entrepreneurship, just transitions, intersectionality and racialized and marginalized communities. Its objective is to shift attention away from an exclusive focus on economic wealth creation to frame a more dynamic understanding of social and emancipatory entrepreneurship as a catalyst for social change with multiple possible outcomes, such as poverty alleviation, the elimination of oppression, and/or decolonization, etc. A significant aim is (i) to encourage research that transcends traditional diversity categories, fostering deeper insights into intersectionality and its impact on entrepreneurship, especially in marginalized and racialized communities, and (ii) explore the unique motivations behind venture creation in context of social and emancipatory entrepreneurship, particularly those ventures aimed at societal change and facilitating just transitions.
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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 | 0.017 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.044 |
| Scholarly communication | 0.021 | 0.020 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".