Fetal Risk, Federal Response: How Fetal Alcohol Syndrome Influenced the Adoption of Alcohol Health Warning Labels
Bibliographic record
Abstract
abstract: In the fifteen years between the discovery of fetal alcohol syndrome (FAS) in 1973 and the passage of alcohol beverage warning labels in 1988, FAS transformed from a medical diagnosis between practitioner and pregnant women to a broader societal risk imbued with political and cultural meaning. I examine how scientific, social, moral, and political narratives dynamically interacted to construct the risk of drinking during pregnancy and the public health response of health warning labels on alcohol. To situate such phenomena I first observe the closest regulatory precedents, the public health responses to thalidomide and cigarettes, which established a federal response to fetal risk. I then examine the history of how the US defined and responded to the social problem of alcoholism, paying particular attention to the role of women in that process. Those chapters inform my discussion of how the US reengaged with alcohol control at the federal level in the last quarter of the twentieth century. In the 1970s, FAS allowed federal agencies to carve out disciplinary authority, but robust public health measures were tempered by uncertainty surrounding issues of bureaucratic authority over labeling, and the mechanism and extent of alcohol’s impact on development. A socially conservative presidency, dramatic budgetary cuts, and increased industry funding reshaped the public health approach to alcoholism in the 1980s. The passage of labeling in 1988 required several conditions: a groundswell of other labeling initiatives that normalized the practice; the classification of other high profile, socially unacceptable alcohol-related behaviors such as drunk driving and youth drinking; and the creation of a dual public health population that faced increased medical, social, and political scrutiny, the pregnant woman and her developing fetus.
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 | 0.009 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".