“Broken Home”: (De)constructing the Moral Standards of Mobility for Atlanta’s Early Black Public Housing Families
Bibliographic record
Abstract
The public housing program was designed as a stepping-stone into upward socioeconomic mobility when the first developments were constructed for White and Black households in the 1930s. White residents were able to save and move into private housing with greater speed than Black residents, who faced both external and internal constraints on their socioeconomic status. As a result of this decreased mobility, scholars and policymakers soon associated public housing developments with impoverished Black containment, categorizing it as the home of the underclass and those who are stuck in place. This article employs a Du Boisian approach to understand the categorical differences and political economic conditions shaping mobility rates among Atlanta’s early Black public housing families. Using historical documents and approximately 40 years of administrative data collected from the first Black public housing development in Atlanta, Georgia by housing managers, Du Bois, and a group of research assistants from Atlanta University, this article examines how internal and external constraints shaped Black tenant mobility. It demonstrates how housing administrators and their actions shaped eviction rates—and by default, public housing’s ability to advance Black tenant mobility—through elite housing managers’ moral judgments of impoverished Black families.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".