Exploring the life histories of black women early career academics in the STEM field within UK higher education institutions.
Bibliographic record
Abstract
This life history-based thesis examines the experiences of six black women early career academics in the STEM field within UK higher education institutions. This thesis explored how the informant’s life stories have been shaped by the intersections of race, gender and neo-liberal discourses. It further locates the informant’s life stories within broader social, political and historical context in which these experiences occurred. \n \nThe life stories of these black women early career academics uncover persisting inequalities based on race and gender differences and the ways in which these informants navigate these unique challenges within UK higher education institutions. It uncovers how these informants’ identities and subjectivities continue to be shaped by their participation in the STEM field within UK higher education institutions. As this thesis examines the informant’s life stories through the theoretical lens of CRT, decolonial thought, coloniality of gender, racial neoliberalism and Bourdieu capital theories. The findings suggest that the informant’s life histories demonstrate how the UK higher education institutions are implicated by race, gender and neo-liberal discourses and how this shapes the STEM field. Thus, it important for relevant stakeholders to consider the racialised and gendered structures and systems within UK higher education in light on the changing demographic of STEM students and academic staff. \n \nThis study is important because it highlight the intersectional inequalities based on race and gender which has not be addressed in previous policy discourses and equality charters. By addressing this issue, there would be increased diversity in STEM field that results in increased research output, products and services useful in society.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.008 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".