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Record W6988168363

We-ness : couple identity as shared by male partners of breast cancer patients

2014· article· en· W6988168363 on OpenAlexaff

Bibliographic record

VenueArca (British Columbia Electronic Library Network) · 2014
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsTrinity Western University
Fundersnot available
KeywordsIdentity (music)Breast cancerContext (archaeology)Phenomenology (philosophy)Lived experiencePersonal identity
DOInot available

Abstract

fetched live from OpenAlex

The present study explored the wider relational context of partners of women facing cancer. Seven male partners of breast cancer patients shared their experience of being a partner to a woman going through cancer. Dialogal phenomenology allowed for clarification of the landscape of these partners' experience by providing opportunity to formulate their experience and to unfold meanings attributed to this experience. Seven themes were identified: crisis and aftermath; children, parenting, and fertility; personal impact; breast cancer as a shared experience; honouring voices and voice; relational choreography; and relational outlook. These men shared different ways that being a partner of a woman with cancer is a shared experience. One pattern that emerged describes how a "you and me" couple identity framework can shift into a "we" perspective. These results revealed how couple identity emerged in relational patterns of engagement during conversational interviewing, a distinctive feature that fits well with previous findings.

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)0.009
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
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.004
Scholarly communication0.0040.003
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.004
GPT teacher head0.219
Teacher spread0.215 · 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
Published2014
Admission routes1
Has abstractyes

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