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Record W2014750983 · doi:10.1002/pon.998

Audience responses to a research‐based drama about life after breast cancer

2005· article· en· W2014750983 on OpenAlexaff
Christina Sinding, Ross E. Gray, Pamela Grassau, Falia Damianakis

Bibliographic record

VenuePsycho-Oncology · 2005
Typearticle
Languageen
FieldArts and Humanities
TopicArtistic and Creative Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDramaBreast cancerDistressIsolation (microbiology)PsychologySurvivorship curveQualitative researchSocial psychologyAestheticsMedicinePsychotherapistSociologyCancerArtLiteratureSocial scienceBioinformaticsBiology

Abstract

fetched live from OpenAlex

This article explores audience reactions to the research-based drama Ladies in Waiting? Life After Breast Cancer. Quantitative findings indicate an overwhelmingly positive response, with approximately 90% of those who saw the production agreeing that they benefited from seeing it and indicating that they would recommend it to others. Qualitative data reveal a more complex picture of the range of reactions, allowing us to describe the most valued aspects of the production (mainly how it eased isolation and normalized the difficult aspects of survivorship) and to better understand the few reports of distress. Audience responses to Ladies in Waiting? suggest that chronic aspects of breast cancer are rarely acknowledged. Viewing the production as one that reveals difficult and hidden realities allows for a fuller understanding both of its supportive and unsettling effects.

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)0.005
metaresearch head score (Gemma)0.021
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 score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0030.002
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0110.001

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 head0.134
GPT teacher head0.459
Teacher spread0.325 · 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

Citations34
Published2005
Admission routes1
Has abstractyes

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