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Record W2076519201 · doi:10.1080/07399330600770254

The Process of Losing and Regaining Credibility When Coming-Out at Midlife

2006· article· en· W2076519201 on OpenAlexaff
Tracey Rickards, Judith Wuest

Bibliographic record

VenueHealth Care For Women International · 2006
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsNew Brunswick Community CollegeGovernment of New BrunswickUniversity of New Brunswick
Fundersnot available
KeywordsCredibilityHealth careProcess (computing)PsychologyGrounded theorySocial psychologyGerontologyNursingSociologyMedicineQualitative researchPolitical scienceComputer scienceSocial science

Abstract

fetched live from OpenAlex

The purpose of this research was to investigate the coming-out process for women at midlife, and to understand how this process of coming-out affects women's health and health care relationships. Using feminist grounded theory, from the interview data we elicited an understanding of how women experienced the coming-out process, how the process influenced their health and health care, what they considered problematic about the process, and how they managed or resolved problematic issues. The basic social process (BSP) of confronting the taken for granted illustrated how the central problem of credibility was experienced. The BSP has three phases: facing scary love, finding me, and settling in. Variables that impact on these phases are support and the concomitant microprocess of enduring perpetual outing. The findings provide a theoretical framework needed for health care providers to understand the coming-out process for midlife women and how it influences their health and health care. The theory provides new insights into the complexity for women transitioning to lesbian at midlife.

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)0.016
metaresearch head score (Gemma)0.041
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 score0.017
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.041
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0170.018
Scholarly communication0.0090.008
Open science0.0020.010
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0040.001

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 head0.028
GPT teacher head0.405
Teacher spread0.377 · 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

Citations15
Published2006
Admission routes1
Has abstractyes

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Same venueHealth Care For Women InternationalSame topicLGBTQ Health, Identity, and PolicyFrench-language works237,207