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Enregistrement W4293490253 · doi:10.1089/heq.2022.0006

Undocumented Americans Need Equitable Language in Worker Training

2022· article· en· W4293490253 sur OpenAlex

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

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Notice bibliographique

RevueHealth Equity · 2022
Typearticle
Langueen
DomaineHealth Professions
ThématiqueOccupational Health and Safety Research
Établissements canadiensYork Central Hospital
Organismes subventionnairesnon disponible
Mots-clésImmigrationCurriculumMedical educationPandemicGerontologyPsychologyMedicineCoronavirus disease 2019 (COVID-19)Public relationsPolitical sciencePedagogyInfectious disease (medical specialty)Disease

Résumé

récupéré en direct d'OpenAlex

Dear Editor: Undocumented immigrant American workers face barriers to adequate safety training and disparities in occupational health.1 The workplace plays a vital role in the lives of all Americans who perform the necessary work that keeps society functioning, including undocumented workers. It is important that workers receive training and education to perform their work safely and in a healthy manner. Since the COVID-19 pandemic, there has been a shift from in-person training and education to virtual platforms due to the need to be socially distant, including occupational health and safety (OHS) training. There was a need to integrate COVID-19 and infectious disease control and prevention curricula into broader worker training programs. Some of those OHS trainings were conducted virtually, despite barriers that existed for many, including immigrants and persons of color, in technological access, comfort, and fluency.2 Undocumented workers, often immigrants and persons of color, filled many of the roles of essential workers, and were disproportionately employed to work in-person during the COVID-19 pandemic in unsafe working conditions and environments.3 It remains unclear the effectiveness of OHS training undocumented workers received in response to the COVID-19 pandemic and in some cases if any OHS training was even offered. Public health practitioners, researchers, and program planners need to further recognize how the COVID-19 pandemic has created changes in training and education for undocumented workers, who were already facing limitations in virtual and in-person services. At a minimum, the language for OHS training needs to be appropriate for the audience and competently delivered by the instructor.4 Language, however, is not just the dialect, for example, English, Spanish, or Vietnamese, but also using the words in a context the trainees understand.5 For example, undocumented workers may fear reporting injuries on the jobsite and unsafe working conditions, despite their right to do so under federal law without employer retaliation. Simply stating a worker can report injuries may not be enough for undocumented workers. Clarifying worker rights against employer retaliation regardless of their documentation status is important and should be emphasized in OHS training programs.1 This is one of many such examples of how language of worker rights to safety and health needs to be equitable to undocumented workers. There is a need to act toward ensuring that language equity is part of OHS training. Instructors need to engage those with lived experiences of undocumented status and advocate for such audiences to support review of curricula. The input of those with lived experiences can provide context and content an instructor may not have otherwise. Instructors should develop and deliver OHS training on a platform and in a language participants understand, provide translation of materials into languages that fit possible target audiences, and use terminology framed in a practical context applicable to the target audience. To do so would better prepare and protect all workers, including our undocumented workers who equally deserve and need safe working conditions and environments.

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,006
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,441
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0060,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0030,000
Communication savante0,0000,000
Science ouverte0,0000,001
Intégrité de la recherche0,0000,002
Charge utile insuffisante (le modèle a refusé de juger)0,0050,000

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.

Tête enseignante Opus0,247
Tête enseignante GPT0,563
Écart entre enseignants0,316 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle