Why Children Die: the report of a pilot confidential enquiry into child death by CEMACH (Confidential Enquiry into Maternal and Child Health)
Bibliographic record
Abstract
The Confidential Enquiry into Maternal and Child Health (CEMACH) has published a report entitled ‘Why Children Die: A Pilot Study’. The report contains the results of a large confidential enquiry into child death across one-third of England, all of Wales and all of Northern Ireland in 2006. The report contains a quantitative analysis of 957 deaths which shows some regional and ethnic variation in death rates. Also despite high rates of pre-existent and perhaps life-limiting illness/disability, most children die in hospital, with only small numbers in hospices. Child suicide rates were higher than expected and only one-quarter of these cases were known to mental health services. The report also contains a qualitative analysis of a sample of cases ( n = 126) which were subjected review by multidisciplinary panels. Avoidable factors were found in 26% and potentially avoidable in a further 43%. A recurring avoidable factor in relation to healthcare was ‘failed recognition of serious illness’ by healthcare workers not trained in paediatrics or not supervised by trained individuals.
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 | 0.043 | 0.080 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 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".