Entrepreneurial Ingenuity Enabled by Information Technology: Insights for Women Entrepreneurship
Bibliographic record
Abstract
We examine how entrepreneurial ingenuity can be facilitated by information technology (IT)-enabled community-based applications, such as multimedia content and online social interaction, to support underserved women entrepreneurs in a context of physical distancing constraints. Many women entrepreneurs have been intensely affected by the COVID-19 pandemic. The entrepreneurial ingenuity perspective maintains that constraints may serve as catalysts for entrepreneurs to pivot, adapt, and identify novel solutions. Using a qualitative approach and the Gioia methodology, we analyze data from interviews with underserved women entrepreneurs in Canada and the United States. We find that IT-enabled community-based applications provide opportunities for women entrepreneurs to develop their entrepreneurial ingenuity by facilitating reflection about their community and personal transformations, awareness of their broader definitions of success, and expression of their economic and social goals. In this way, this study extends knowledge on the entrepreneurial ingenuity perspective and thereby brings new theorizing to enrich the information systems theoretical literature.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".