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Record W4416275354 · doi:10.2196/83401

Hidden Workers in Aging Australia: Protocol of Intersectionality-Informed Mixed Methods Study

2025· article· en· W4416275354 on OpenAlex
Sora Lee, Lu Yang, Mehak Batra

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDiscrimination and Equality Law
Canadian institutionsnot available
Fundersnot available
KeywordsProtocol (science)Data collectionProtocol analysismHealthResearch design

Abstract

fetched live from OpenAlex

BACKGROUND: Australians are living longer and are expected to remain in the workforce for longer; yet, many older adults struggle to secure employment despite being willing and able to work. A growing share of these individuals are "hidden workers," those underused in the labor market due to missed hours, long-term unemployment, or withdrawal from job seeking despite the capacity to work. This group reflects a global trend of aging yet underused workforces, and in Australia, they represent a significant proportion of the working-age population. Addressing the challenges of hidden workers is crucial, as their inclusion could help meet labor market demands, alleviate fiscal pressures of aging, and promote healthier, more equitable aging trajectories. OBJECTIVE: This intersectional mixed methods study has 3 overarching aims. First, to investigate how intersecting social identities (eg, age, gender, cultural background, health status, and caregiving responsibilities) shape hidden workforce participation and associated health outcomes among aging Australians. Second, to compare hidden workers with currently employed populations in order to identify health discrepancies between the 2 groups. Third, to explore the lived experiences of hidden workers, focusing on how intersecting and multiply disadvantaged identities impose additional burdens on employment outcomes and health status. Together, these aims will generate an integrated understanding of both structural and lived dimensions of hidden work, providing evidence to inform more equitable labor market and health policies. METHODS: This study uses an explanatory sequential mixed methods design to investigate the health, resources, and employment experiences of aging hidden workers in Australia. In phase 1, an online cross-sectional survey was administered to 1166 participants (696 hidden workers aged more than 45 years and 470 current workers), capturing variables on employment history, health, discrimination, workplace social capital, caregiving, and socioeconomic status. Validated instruments, including the Workplace Age Discrimination Scale, Intersectional Anticipated Discrimination Scale, and Workplace Social Capital Index, were incorporated to ensure reliability. Phase 2 will involve semistructured interviews with a purposive subsample (30 participants) identified from survey results, focusing on lived experiences of workforce exclusion and intersecting barriers. In phase 3, quantitative and qualitative findings will be integrated through triangulation and complementarity to provide a comprehensive understanding of hidden workers' challenges and assets, generating evidence to inform policy and stakeholder recommendations. RESULTS: As of September 2025, the online survey has been completed, phase 2 interviews are underway, and phase 3 integration is scheduled for completion by mid-2026. CONCLUSIONS: This study will generate the first intersectional evidence on the health and employment challenges of hidden aging workers in Australia. These insights will inform tailored policy interventions that can support re-engagement, reduce inequities in health and well-being, and strengthen workforce participation. Ultimately, the findings will contribute to addressing skills shortages while promoting social and economic inclusion of aging Australians. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/83401.

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.

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)0.014
metaresearch head score (Gemma)0.002
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.481
Threshold uncertainty score0.938

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.536
GPT teacher head0.718
Teacher spread0.181 · 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