Pregnancy information and advice on Sky television: an evaluation
Bibliographic record
Abstract
This paper is one of a series produced as part of an evaluation of a number of digital interactive television (DiTV) health pilots funded by the Department of Health during 2001/2002. This paper is concerned with two pregnancy health services produced by Channel Health and hosted on Sky television. The study aimed to discover the success or otherwise of health information on pregnancy in this form and on this medium or "platform". In particular we were interested in what kinds of people on the broader national stage viewed the Bush Babies programme. Data were obtained through a telephone questionnaire of Channel Health users. More than 250 people took part. More than 175 000 households watched the programmes, a large audience for this type of programme. Bush Babies attracted a sizeable audience with over a quarter of Channel Health viewers in this study having seen it. There proved to be marked differences between the types of people using the service and in the patterns of their use--and not always in the ways one might have expected. As expected, people who were single, older or male were less likely to view Bush Babies, while younger, married or cohabitants and females were more likely to watch the programme. More unexpectedly, perhaps, the fact that the person was pregnant was not a predictor of whether they saw a Bush Babies programme or the number of the programmes watched.
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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 | 0.020 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".