Through a Colored Looking Glass: A View of Judicial Partition, Family Land Loss, and Rule Setting
Bibliographic record
Abstract
African Americans in contemporary U.S. society continue to experience economic inequality. Regardless of the indicators one reviews—property ownership, employment, or income—the data confirm the entrenchment of African Americans’ disadvantaged status. It is the thesis of this Article that the economically subordinated status of African Americans cannot be divorced from the historical processes that have created or contributed to the divide between African Americans and other social groups. In this Article, I explore the struggle of ex-slaves and their twenty-first century descendants to achieve the promise of property in a democratic society and the role of law as a reflection of and tool of racial hierarchy. I focus on the role played by the judicial partition process in creating a system that inextricably led to stripping African Americans of their property. In recent years, courts and legislatures have scrutinized and expressed increasing hostility toward exercises of regulatory power that effect takings. This Article gives a similar scrutiny to the partition process and argues that it should be modified to alleviate the unfair burden it places on poor property owners and to assure that property owners are afforded just compensation when their property is involuntarily taken to achieve a public purpose.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.079 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".