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Record W3165421531 · doi:10.1017/s071498082100012x

Long-Term Care Facility Workers’ Perceptions of the Impact of Subcontracting on their Conditions of Work and the Quality of Care: A Qualitative Study in British Columbia, Canada

2021· article· en· W3165421531 on OpenAlexafffundabout
Albert Banerjee, Margaret J. McGregor, Sage Ponder, Andrew Longhurst

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2021
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsSimon Fraser UniversityVancouver Coastal HealthVancouver Coastal Health Research InstituteSt. Thomas University
FundersUniversity of British ColumbiaFondation de la recherche en santé du Nouveau-Brunswick
KeywordsWorkloadFlexibility (engineering)Work (physics)BusinessQuality (philosophy)Qualitative researchPerspective (graphical)Long-term careNursingLabour economicsMedicineEconomicsManagementSociology

Abstract

fetched live from OpenAlex

Subcontracting long-term care (LTC), whereby facilities contracted with third party agencies to provide care to residents, became widespread in British Columbia after 2002. This qualitative study aimed to understand the impact of subcontracting from the perspective of care workers. We interviewed 11 care workers employed in subcontracted facilities to explore their perceptions of caring and working under these conditions. Our overarching finding was one of loss. Care workers lost wages, benefits, security, and voice. Their working conditions worsened, with workload and turnover increasing, resulting in a loss of experienced staff and a loss of time to provide care. These findings call into question the promises of quality and flexibility that legitimated policies permitting subcontracting, while adding to the mounting evidence that subcontracting LTC harms both workers and residents.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.292

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0190.010
Scholarly communication0.0040.001
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.343
Teacher spread0.320 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations8
Published2021
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal on Aging / La Revue canadienne du vieillissementSame topicGeriatric Care and Nursing HomesFrench-language works237,207