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Record W1828178760 · doi:10.1111/hsc.12299

Disabled and elderly citizens' perceptions and experiences of voluntarism as an alternative to publically financed care in the Netherlands

2015· article· en· W1828178760 on OpenAlexfundno aff
Ellen Grootegoed, Evelien Tonkens

Bibliographic record

VenueHealth & Social Care in the Community · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsnot available
FundersMinisterie van Volksgezondheid, Welzijn en SportOntario Ministry of Health and Long-Term Care
KeywordsVoluntarism (philosophy)WelfareFeelingSocial isolationPerceptionPublic relationsAffect (linguistics)Social recognitionPolitical scienceIsolation (microbiology)Animal welfareSocial WelfarePsychologySocial psychologyLawPsychiatry

Abstract

fetched live from OpenAlex

Many European welfare states are replacing comprehensive welfare schemes with selective and conditional entitlements. Such changes affect the recognition of vulnerable citizens' needs, which are increasingly framed as private responsibilities to be met by the voluntary sector. Repeated interviews with 30 clients affected by cutbacks to publicly financed (day)care in the Netherlands show that although disabled and elderly citizens are often hesitant to open their doors to volunteers, they do experiment with voluntarism to reduce their social isolation, both by receiving voluntary care and by engaging in volunteer work themselves. However, the turn to voluntarism does not always prompt recognition of the needs of vulnerable citizens. This study signals how disappointing and sometimes demeaning experiences with volunteers can increase feeling of misrecognition. We conclude that the virtues of voluntarism may be overstated by policy makers and that the bases of recognition should be reconsidered as welfare states implement reform.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.273
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
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 head0.089
GPT teacher head0.430
Teacher spread0.341 · 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.

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

Citations11
Published2015
Admission routes1
Has abstractyes

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