Changes in the Prevalence of Nonstandard Employment during the COVID-19 Pandemic
Notice bibliographique
Résumé
This paper addressed two research questions related to employment throughout the COVID-19 pandemic. First, how did the prevalence of different types of nonstandard employment change before and during the COVID-19 pandemic? Second, how did these changes differ by gender, immigration status, and age group? These questions are important to understanding how economic uncertainty and downturn may impact the types of employment that workers enter and who is impacted. This study pools together 10 Canadian Labour Force Surveys from May 2017 to November 2021 and employs a multivariate linear regression analysis to answer the previously stated research objectives. Within these regression models, we examined the likelihood of entering temporary employment, part-time employment, and nonstandard self-employment before and throughout the pandemic. We also ran several interaction models to test whether changes to different types of nonstandard employment differed by sex, immigration status, and age. These interactions tested whether the likelihood of nonstandard employment differs by each demographic group before and during the pandemic. The findings demonstrate that the COVID-19 pandemic differed from previous economic crises in its impact on nonstandard employment. The main finding was that rates of nonstandard wage work (temporary and part-time employment) decreased during the first initial lockdown and returned to pre-pandemic levels by the end of 2020. Meanwhile, own-account and part-time self-employment increased during the first wave of the pandemic. During the first few months of the pandemic, the rate of nonstandard employment had a narrower gender gap and a wider immigrant/non-immigrant gap. There is also some evidence that the nonstandard self-employment rate increased among immigrants and women during the first few months.AbstractThe COVID-19 pandemic has drastically impacted employment across Canada. While several reports show an increase in job loss and unemployment, there is little mention of changes in types of employment during the pandemic. Drawing on the Canadian Labour Force Surveys from 2017-2021, this article explored how the pandemic affected nonstandard employment rates while examining whether these impacts differed by certain sociodemographic variables. Namely, differences in rates of nonstandard employment were explored by gender, immigrant status, and age group. The main finding was that rates of nonstandard wage work (temporary and part-time employment) decreased during the first initial lockdown and returned to pre-pandemic levels by the end of 2020. Meanwhile, own-account and part-time self-employment increased during the first wave of the pandemic. While these increases were uniformly experienced across different groups of workers, there is some evidence of widening or narrowing gaps in rates of nonstandard employment depending on the sociodemographic group.
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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 | 0,001 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 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 ».