Bibliographic record
Abstract
This thesis examines how dominant and exclusionary design practices operate within systems of power, how these maintain experiences of privilege and oppression, and how these might be challenged through a systematic implementation of intersectional feminist thought in design processes.A three-phased qualitative study was conducted.Phase 1 involves a critical literature review of intersectionality and how forms of dominant design operate, including the Double Diamond model.Phase 2 includes an analysis of three design approaches, Design Justice, Data Feminism and Towards an Intentional Intersectional Practice to assess the implementation of intersectionality in the design process.Phase 3 synthesizes the findings and discusses how intersectional thinking may counteract dominant design.It was discovered that emerging intersectional feminist design approaches contribute to counteracting dominant design.This work is fledgling and further study is required to systematically implement intersectional feminist thought in design processes.This thesis offers insight regarding how to do so.
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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 | 0.066 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.016 | 0.105 |
| Scholarly communication | 0.018 | 0.019 |
| Open science | 0.003 | 0.027 |
| Research integrity | 0.003 | 0.007 |
| 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".