Republican Rules of Reproduction and “Flipping the Script” on U.S. Health Care Reform
Bibliographic record
Abstract
Given the relatively conservative and marketized nature of U.S. health care reform, it remains unclear both why Republican resistance has been so intractable through much of the Affordable Care Act's (ACA's) tenure and why it has so suddenly receded into the background. This article seeks an explanatory mechanism to make sense of the ACA's changing historical fortunes, from enactment to the present. It argues that the Republican Party's “rules of reproduction,” a concept of historical sociology, best explains why the ACA met with such vociferous resistance and why that resistance has given way to surprising progress on coverage. It begins with a consideration of marketized U.S. health care, as well as the ACA's quest for expanded coverage—not structural rearrangement—as the basis for progressive change. Following this, I explore the “rules of reproduction” to explain Republican political actors’ relentless attacks on the law. The final section considers how the historically-contingent COVID-19 event has dovetailed with ACA entrenchment, effectively “flipping the script” on Republican rules, making anti-Obamacare maneuvers far less politically palatable. It is in this political space that reform advocates have been able to seize opportunity and broaden access.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.041 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 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".