Women’s representation in business case studies – a framework of postmodernism to uncover hidden assumptions
Bibliographic record
Abstract
A review of entrepreneurship literature indicates a gap in women representation in business pedagogy. Studies emphasise the importance of business schools and effective curriculum in influencing potential entrepreneurs in venture creation. To identify the gap of women representation and to evaluate the effectiveness of curriculum materials, the paper examines the role of pedagogical materials used in entrepreneurship programmes to develop more women entrepreneurs. The lack of an integrative framework for understanding the nature and implications of women representation related to issues of power and dominance, ‘white male privileges’ in decision-making, and representation of marginalised groups are hardly studied. The study used a framework of postmodernism to help inform and interpret past research and frame the research problem and discussion. The paper compared and critically examined the assumptions made in case studies of a widely used entrepreneurship textbook and used deconstruction to understand women's representation and portrayal in case studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.071 | 0.079 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.005 | 0.021 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".