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Record W6958772184 · doi:10.6084/m9.figshare.27605044

Using Ecological Momentary Analysis to explore stigma experiences in the real world for adults with acquired hearing loss

2024· article· en· W6958772184 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural pest management studies
Canadian institutionsnot available
Fundersnot available
KeywordsActive listeningStigma (botany)Hearing lossSocial isolationQuarter (Canadian coin)Social stigmaYoung adult

Abstract

fetched live from OpenAlex

The aim of this study was to use Ecological Momentary Assessment (EMA) to capture how stigma-induced identity threat is experienced by adults with hearing loss and how they respond to such threats in daily life. Twenty adults with hearing loss from 53 to 88 years (mean age of 69.4 years) completed a range of demographic and stigma questionnaires in the laboratory and, over a two-week period, answered daily EMA surveys. A total of 633 EMA surveys were collected. Five participants reported 13 listening events in which they experienced stigma. These events were typically when conversing with family or friends who were aware of the adults’ hearing loss. The number of individual stigma experiences captured by EMA were low, when viewed across a large number of social interactions. However, as a group, a quarter of the participants in this study experienced stigma over a two-week period, typically from others close to them. This suggests that stigma experiences may be a regular occurrence for some adults with hearing loss.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.164
GPT teacher head0.310
Teacher spread0.146 · 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 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
Published2024
Admission routes1
Has abstractyes

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