Unregulated, Unknown and Highly Necessary: Grey Market Nannies

Canada’s robust yet overburdened public childcare drives reliance on a “grey market” of nannies and private caregivers, often mediated by digital gig platforms. This paper analyzes over 6,000 nanny profiles scraped from CanadianNanny.ca in the Greater Toronto–Hamilton area to investigate how platform-enabled self-presentation reproduces inequality in care labour. Using natural language processing (sentiment, n-gram, and LDA topic modeling), we find a stratified market where self-presentation diverges by wage tier. Lower-wage caregivers (under $20/hour) disproportionately frame themselves as "generalists," bundling childcare with extensive domestic labour (housekeeping, meals). In contrast, higher-wage caregivers (over $20/hour) emphasize professional credentials, specialized skills (e.g., newborn care), and formal training. These results show that digital platforms actively structure care labour, reinforcing racialized and gendered hierarchies that devalue generalist labour while conditionally valorizing professionalized care. We argue that Canada’s fragmented system entrenches this dual process, the devaluation of reproductive labour for the many and conditional valorization for the few, underscoring the urgent need for policy to regulate platform work and ensure equitable recognition and protection for all care workers.

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Publication Details

Published
2025-09-27
DOI
https://doi.org/10.31235/osf.io/bsmzy_v1
Primary Topic
Digital Economy and Work Transformation
Type
article
Field-Weighted Citation Impact
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article

Unregulated, Unknown and Highly Necessary: Grey Market Nannies

Monica J. Alexander, Fabio Robibaro
Digital Economy and Work Transformation
article

Unregulated, Unknown and Highly Necessary: Grey Market Nannies

Monica J. Alexander, Fabio Robibaro
article en

Abstract

Canada’s robust yet overburdened public childcare drives reliance on a “grey market” of nannies and private caregivers, often mediated by digital gig platforms. This paper analyzes over 6,000 nanny profiles scraped from CanadianNanny.ca in the Greater Toronto–Hamilton area to investigate how platform-enabled self-presentation reproduces inequality in care labour. Using natural language processing (sentiment, n-gram, and LDA topic modeling), we find a stratified market where self-presentation diverges by wage tier. Lower-wage caregivers (under $20/hour) disproportionately frame themselves as "generalists," bundling childcare with extensive domestic labour (housekeeping, meals). In contrast, higher-wage caregivers (over $20/hour) emphasize professional credentials, specialized skills (e.g., newborn care), and formal training. These results show that digital platforms actively structure care labour, reinforcing racialized and gendered hierarchies that devalue generalist labour while conditionally valorizing professionalized care. We argue that Canada’s fragmented system entrenches this dual process, the devaluation of reproductive labour for the many and conditional valorization for the few, underscoring the urgent need for policy to regulate platform work and ensure equitable recognition and protection for all care workers.

Openalex Percentile: Top 65%
Digital Economy and Work Transformation
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