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Record W4408509107 · doi:10.3138/cjc-2024-0021

The Gig Economy of Care: Analyzing “The Airbnb of Eldercare” and Its Policy Implications in British Columbia

2025· article· en· W4408509107 on OpenAlexaffvenueabout
Alicia Massie, Kayla Hilstob

Bibliographic record

VenueCanadian Journal of Communication · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsGig economySharing economyAged careBusinessPolitical scienceEconomicsEconomyGerontologyMedicineLaw

Abstract

fetched live from OpenAlex

Background: This study critically analyzes the impact of platform capitalism on elder care in British Columbia, focusing on Tuktu, an app-based tech startup that mediates care services through digital platforms. Analysis: Using feminist and intersectional theory, we explore how Tuktu’s business model commodifies care and exploits care workers by misclassifying them as independent contractors and stripping them of labour rights and protections. Conclusions and implications: We advocate for comprehensive policy reforms that ensure equitable labour standards, uphold the dignity of care recipients, and promote community-based care solutions. The study also calls for stronger regulation of digital platforms in the care economy, ensuring that the integration of technology enhances, rather than undermines, the quality of care and labour conditions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.806
Threshold uncertainty score0.857

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.260
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes3
Has abstractyes

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