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Record W3119306690 · doi:10.1080/00324728.2020.1854332

Errors in reported ages and dates in surveys of adult mortality: A record linkage study in Niakhar (Senegal)

2021· article· en· W3119306690 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePopulation Studies · 2021
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsUniversity of Ottawa
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentAgence Nationale de la Recherche
KeywordsSiblingDemographyMedicineRecord linkageRecallLinkage (software)Recall biasEnvironmental healthPopulationPsychology

Abstract

fetched live from OpenAlex

Sibling survival histories are a major source of adult mortality estimates in countries with incomplete death registration. We evaluate age and date reporting errors in sibling histories collected during a validation study in the Niakhar Health and Demographic Surveillance System (Senegal). Participants were randomly assigned to either the Demographic and Health Survey questionnaire or a questionnaire incorporating an event history calendar, recall cues, and increased probing strategies. We linked 60-62 per cent of survey reports of siblings to the reference database using manual and probabilistic approaches. Both questionnaires showed high sensitivity (>96 per cent) and specificity (>97 per cent) in recording siblings' vital status. Respondents underestimated the age of living siblings, and age at and time since death of deceased siblings. These reporting errors introduced downward biases in mortality estimates. The revised questionnaire improved reporting of age of living siblings but not of age at or timing of deaths.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.100
GPT teacher head0.406
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it