MétaCan
Menu
Back to cohort
Record W2913829995 · doi:10.1177/1049732318825150

Reformulating the Worker Identity: Men’s Experiences After Radical Prostatectomy

2019· article· en· W2913829995 on OpenAlexafffundabout
Wellam F. Yu Ko, John L. Oliffe, Joy L. Johnson, Joan L. Bottorff

Bibliographic record

VenueQualitative Health Research · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicGender Roles and Identity Studies
Canadian institutionsSimon Fraser UniversityOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsProstatectomyContext (archaeology)WorkforceGrounded theoryConstructivist grounded theoryIdentity (music)Work (physics)Qualitative researchMedicineProstate cancerPsychologySociologyPolitical scienceCancerSocial scienceEngineering

Abstract

fetched live from OpenAlex

The number of men in the Canadian workforce who have prostate cancer is increasing. The purpose of the study was to explore the processes involved in men’s return to work post radical prostatectomy and understand how these events are connected to masculinities. Drawing on data collected through individual interviews with 24 participants, constructivist grounded theory method was used to develop the substantive theory of Reformulating the Worker Identity which comprises two processes, recovering after radical prostatectomy and renegotiating work expectations. Recovering after radical prostatectomy revealed how men overcame side effects at home and evaluated their potential for returning to work. Renegotiating work expectations included participant’s strategies for securing graduated return to work accommodations. Study findings revealed that the challenges for fully returning to work post prostatectomy are often underestimated by clinicians and patients. In this context, preempting return to work challenges preoperatively might allay significant anxieties for many men.

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)0.022
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.323
GPT teacher head0.593
Teacher spread0.270 · 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.

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

Citations9
Published2019
Admission routes3
Has abstractyes

Explore more

Same venueQualitative Health ResearchSame topicGender Roles and Identity StudiesFrench-language works237,207