An analysis of Covid-19 deaths and equality in Northern Ireland.
Bibliographic record
Abstract
ObjectivesThe overarching aim is to extend understanding of Covid-19 and non Covid-19 mortality during the pandemic. For the first two waves of the pandemic in Northern Ireland, the study addressed evidence gaps for both Covid-19 and non Covid-19 deaths in relation to equality group, health and socio-demographic characteristics. ApproachPrior to this research, mortality analyses in Northern Ireland during the pandemic had been largely based on information recorded on death certificates and information gaps remained. This research linked death records to extensive socio-demographic, health and equality group information, retrieved from the 2011 Census, providing a more comprehensive assessment of mortality. The research approach demonstrated innovative use of linked datasets in support of public policy. Findings also complement similar analysis published by the Office for National Statistics (ONS). Research questions were shaped and informed by information queries from a range of stakeholders including the Department of Health and elected officials. ResultsResults published to date are based on Covid-19 and non Covid-19 deaths occurring in the 7-month period between 1st March 2020 and 30th September 2020. We found that there was a 48% and 40% higher risk for persons self-reporting having a disability at the time of the 2011 Census (compared to ‘non-disabled’ people) for Covid-19 and non Covid-19 mortality respectively. After accounting for differences in age, sex and area of residence, there was no significant difference in risk of Covid-19 death, for the time period March to September 2020, for those who identified as Catholic at the time of the 2011 Census, compared to Protestants and other Christians. ConclusionThe research addresses priority evidence gaps identified by government officials and third sector policy leads. The depth of commentary provided within the report is enabling researchers and policy makers to gain greater familiarity with a key research resource. This will be instrumental in shaping future research through ADR Northern Ireland.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".