Capturing and Documenting the Wider Health Impacts of the COVID-19 Pandemic Through the Remember Rebuild Saskatchewan Initiative: Protocol for a Mixed Methods Interdisciplinary Project
Notice bibliographique
Résumé
BACKGROUND: In the Canadian province of Saskatchewan, the global COVID-19 pandemic appeared amidst existing social health challenges in food insecurity, housing precarity and homelessness, poor mental health, and substance misuse. These chronic features intersected with the pandemic, producing a moment in time when the urgency of COVID-19 brought attention to underlying shortcomings in public health services. OBJECTIVE: The objectives of the program of research are (1) to identify and measure relationships between the pandemic and wider health and social impacts, namely, food insecurity, housing precarity and homelessness, and mental health and substance use in Saskatchewan, and (2) to create an oral history of the pandemic in Saskatchewan in an accessible digital public archive. METHODS: We are using a mixed methods approach to identify the impacts of the pandemic on specific equity-seeking groups and areas of social health concern by developing cross-sectional population-based surveys and producing results based on statistical analysis. We augmented the quantitative analysis by conducting qualitative interviews and oral histories to generate more granular details of people's experiences of the pandemic. We are focusing on frontline workers, other service providers, and individuals within equity-seeking groups. We are capturing digital evidence and social media posts; we are collecting and organizing key threads using a free open-source research tool, Zotero, to trace the digital evidence of the pandemic in Saskatchewan. This study is approved by the Research Ethics Board at the University of Saskatchewan (Beh-1945). RESULTS: Funding for this program of research was received in March and April 2022. Survey data were collected between July and November 2022. The collection of oral histories began in June 2022 and concluded in March 2023. In total, 30 oral histories have been collected at the time of this writing. Qualitative interviews began in April 2022 and will continue until March 2024. Survey analysis began in January 2023, and results are expected to be published in mid-2023. All data and stories collected in this work are archived for preservation and freely accessible on the Remember Rebuild Saskatchewan project's website. We will share results in academic journals and conferences, town halls and community gatherings, social and digital media reports, and through collaborative exhibitions with public library systems. CONCLUSIONS: The pandemic's ephemeral nature poses a risk of us "forgetting" this moment and the attendant social inequities. These challenges inspired a novel fusion among health researchers, historians, librarians, and service providers in the creation of the Remember Rebuild Saskatchewan project, which focuses on preserving the legacy of the pandemic and capturing data to support an equitable recovery in Saskatchewan. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/46643.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,090 | 0,061 |
| Méta-épidémiologie (sens strict) | 0,004 | 0,004 |
| Méta-épidémiologie (sens large) | 0,003 | 0,004 |
| Bibliométrie | 0,005 | 0,005 |
| Études des sciences et des technologies | 0,010 | 0,005 |
| Communication savante | 0,007 | 0,004 |
| Science ouverte | 0,006 | 0,007 |
| Intégrité de la recherche | 0,005 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,068 | 0,015 |
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 source (Gemma direct ou Codex distillé), 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 ».