White spaces: how marketing actors (re)produce marketplace inequities for Black consumers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper interrogates how racially discriminatory practices by real estate agents, lenders, and retailers produce and reproduce marketplace inequities for Black consumers. Drawing on Critical Race Theory (CRT) and interdisciplinary research, the paper reveals the normalisation and permanence of racism in practices and policies aimed at protecting White spaces. Marketing actors racially discriminatory approaches have morphed from overt to more covert strategies, but they persist in spite of regulatory changes. Impacts on Black consumers have created profound marketplace inequities including constricted and restricted choices, devalued housing assets, housing segregation, retail discrimination, restricted and expensive access to credit, wealth gaps, and retail desertification. When viewed through a CRT lens, we conclude that in the American context, the invisible hand of the market is not invisible. Rather, it is White. The study draws implications for practice, and urgently calls for more research to unmask racism in marketing – because Black Lives Matter!
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.
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 | 0.023 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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 it