Bibliographic record
Abstract
Since it was first described in the medical literature in 1968, Fetal Alcohol Syndrome (FAS) has become recognized as the leading cause of preventable birth defects in Canada. As a diagnostic category, FAS refers to the teratogenic affects of alcohol which result in facial anomalies, growth deficiencies, and central nervous system dysfunction. The portrayals of FAS in the mass media, and elsewhere in the popular realm, indicate that FAS does not simply exist as a diagnostic category. Persons with FAS seem to be portrayed as tragedies and social deviants who place an economic burden on society. The mothers who give birth to children born with FAS are seen as irresponsible and in need of surveillance. Troubled by what the author perceived as oppressive representations of persons with FAS and their biological mothers, the present study set-out to investigate the portrayal of mothers in popular and professional discourse about Fetal Alcohol Syndrome. Semi-structured interviews, clinical observations, and an analysis of educational material and information in the mass media, were the tools of inquiry used to uncover what is said about FAS and mothers in the professional realms of medicine and social services, and in the popular realms of the mass media, educational material and the internet. Regarding and analyzing FAS as discourse reveals the multiple and contested meanings that are associated with that term. A number of processes and discourses interact to produce a shroud over mothers of children with FAS. Systems problems within the medical and social service sectors, the ambivalence surrounding FAS as a diagnostic category, and ideologies and values attached to the fetus, to mothers, and to alcohol all contribute to an eclipsing of mothers within the discourse of FAS.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.025 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".