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Record W2900282083 · doi:10.1093/geroni/igy023.3228

THE EXPERIENCE OF STIGMA IN CARE PARTNERS OF PEOPLE WITH DEMENTIA - RESULTS FROM AN EXPLORATORY STUDY

2018· article· en· W2900282083 on OpenAlexaff
L A Harper, Bonnie Dobbs, Heather Royan, T Moorth

Bibliographic record

VenueInnovation in Aging · 2018
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsMisericordia Community HospitalUniversity of AlbertaCovenant Health
Fundersnot available
KeywordsDementiaStigma (botany)Coping (psychology)PsychologyExploratory researchClinical psychologyMedicinePsychiatryDisease

Abstract

fetched live from OpenAlex

Stigma has been identified as being central to the experience of having a dementia, both for the person with dementia (PwD) and for their care partners. Despite this growing recognition, we still know very little about the area. Our objectives were to identify the types and degree of stigma experienced by care partners of PwD, identify PwD and care partner variables that may influence the effect of care partner stigma, and determine if there are styles of coping that are associated with dementia stigma. Results indicate that care partners (N=20) report experiencing three types of stigma (stigma by association, lay person’s stigma, and structural stigma). Trends in the data indicate that several types of coping styles are associated with these types of stigma. Only care partner’s education was positively associated with structural stigma. Helping care partners to develop better coping styles may reduce the powerful effect of stigma.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.007
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.084
GPT teacher head0.439
Teacher spread0.355 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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