The Production of the Female Entrepreneurial Subject: A Space of Exclusion for Women of Color?
Bibliographic record
Abstract
SUMMARY Using critical discourse analysis, this paper examines how the female entrepreneurial subject is constructed/produced within entrepreneurial discourses, how this subject is racialized, gendered and classed, and examines what practices contribute to the shaping of the female entrepreneurial subject. I specifically look at four areas/discourses central to entrepreneurship; that of independence, self-definition/self-monitoring, networking, and women's abilities as businesswomen. I contend that contemporary self-employment discourses mirror those of neo-liberalism/modernization where the notion of the independent liberal subject has the ability to self-determine and self-monitor, which is a sign of autonomy and mastery of the self. I also argue that the space of women's entrepreneurship legitimizes white middle-class women's experiences and excludes women of color from becoming active subjects in entrepreneurial discourses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".