Bibliographic record
Abstract
(Excerpt) The egalitarian voice of the U.S. Supreme Court resonates forty years after it abolished antimiscegenation laws in Loving v. Virginia. While Loving's vigor influences contemporary debates on sex-related marriage restrictions, its impact extends to the hopes and tensions that undergird and unite equality movements. Half a world away, Norway's Corporate Board Quota (CBQ), recently began enforcing a forty percent floor for both sexes on publicly traded companies' boards of directors. At first glance, Loving's affirmation of an interracial marriage in the face of the state's opprobrium seems impossibly divergent from the CBQ. Loving concerned de jure racial discrimination while the CBQ remedies de facto corporate gender inequality. Loving also struck down state-sanctioned criminal penalties for interracial marriage, while the CBQ aims at the private sector. Loving is the prototypical test-case litigation, complete with the perfectly named plaintiff and a compelling story. In contrast, the CBQ coldly regulates publicly listed corporations. Finally, and perhaps most significantly, race and gender inequality remedies differ sharply from one another. Even so, parallels exist between Loving and the CBQ. Both attempt to subvert inequalities—marriage's restriction on same-race couples and corporate leadership's maleness. Each also involves government attempts to insert equality into inherently "private," yet state-defined, institutions. Given these consistencies, present-day attempts to remedy inequality, such as the CBQ, reflect the purchase Loving still carries.
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.
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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.020 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.011 | 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".