Using Death Certificates and Medical Examiner Records for Adolescent Occupational Fatality Surveillance and Research: A Case Study
Notice bibliographique
Résumé
Death certificates and medical examiner records have been useful yet imperfect data sources for work-related fatality research and surveillance among adult workers. It is unclear whether this holds for work-related fatalities among adolescent workers who suffer unique detection challenges in part because they are not often thought of as workers. This study investigated the utility of using these data sources for surveillance and research pertaining to adolescent work-related fatalities. Using the state of North Carolina as a case study, we analyzed data from the death certificates and medical examiner records of all work-related fatalities data among 11- to 17-year-olds between 1990-2008 (N = 31). We compared data sources on case identification, of completeness, and consistency information. Variables examined included those on the injury (e.g., means), occurrence (e.g., place), demographics, and employment (e.g., occupation). Medical examiner records (90%) were more likely than death certificates (71%) to identify adolescent work-related fatalities. Data completeness was generally high yet varied between sources. The most marked difference being that in medical examiner records, type of business/industry and occupation were complete in 72 and 67% of cases, respectively, while on the death certificates these fields were complete in 90 and 97% of cases, respectively. Taking the two sources together, each field was complete in upward of 94% of cases. Although completeness was high, data were not always of good quality and sometimes conflicted across sources. In many cases, the decedent's occupation was misclassified as "student" and their employer as "school" on the death certificate. Even though each source has its weaknesses, medical examiner records and death certificates, especially when used together, can be useful for conducting surveillance and research on adolescent work-related fatalities. However, extra care is needed by data recorders to ensure that occupation and employer are properly coded when dealing with adolescent worker deaths.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».