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Record W2316656631 · doi:10.1097/ncc.0000000000000344

An Abundance of Selves

2016· article· en· W2316656631 on OpenAlexaff
Chad Hammond, Ulrich Teucher

Bibliographic record

VenueCancer Nursing · 2016
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsNarrativePsychosocialFeelingIdentity (music)NegotiationThematic analysisNarrative inquiryMedicineEmpowermentQualitative researchPsychologyGender studiesSocial psychologyPsychotherapistSociologyAestheticsPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Identity negotiations of people living with cancer have been shown to be significant psychosocial challenges throughout cancer trajectories but have not been adequately explored among young adults with cancer. Narrative approaches might help to reveal moments of (dis)empowerment that affect their identity negotiations. OBJECTIVE: The aim of this study is to explore how young adults speak to their identities in relation to their narratives of having cancer and receiving care. METHODS: A total of 21 young adults (18-45 years old) provided cancer narratives through semistructured life history interviews. Thematic narrative analysis was used to determine how participants represented themselves in their stories. RESULTS: Participants used a wide diversity of identities well beyond those most familiar in dominant discourses (eg, patients, survivors, and fighters), and their identities frequently changed at significant "turning points" in their narratives, especially in relation to good and bad experiences of care. CONCLUSIONS: Cancer-related identities often undergo personal and social negotiation over time, and not just among young adults still feeling the effects of treatment. Psychosocial oncology could take further steps toward incorporating this fluidity and multiplicity within the discipline's discourses of identity. IMPLICATIONS FOR PRACTICE: The identities gathered here may contribute to a more comprehensive toolkit of narrative resources for empowering young adults (and others) with cancer, serving as a starting point for negotiating identities with their care providers. Our findings raise questions about which identities should be fostered and how healthcare professionals might be (unknowingly) involved in patients' identity negotiations.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.627
Threshold uncertainty score0.335

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.036
GPT teacher head0.385
Teacher spread0.349 · 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.

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

Citations13
Published2016
Admission routes1
Has abstractyes

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