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Analyzing Qualitative Data about Hospitalized Children: Reflections on Bodily Expressions

2014· article· en· W128235071 on OpenAlexafffund
Coralee McLaren

Bibliographic record

VenueThe Qualitative Report · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health ResearchHospital for Sick Children
KeywordsGazePsychologyQualitative researchEnergy (signal processing)Health careNursingDevelopmental psychologyApplied psychologyMedicineSociology

Abstract

fetched live from OpenAlex

Although considerable energy is invested in ensuring that pediatric hospital environments are psychosocially supportive, few researchers have connected the experiences of patients to hospital architecture, a crucial interface between healthcare delivery and patient care. Seeking to uncover childrens experiences within a contemporary hospital, I draw on data gathered during a photo walking tour with hospitalized children. Findings suggest that in addition to speaking, children express themselves physically by appropriating the gaze, pressing boundaries and finding alternate spaces. New methods and techniques are needed to reveal childrens physical competencies and abilities to determine their environmental preferences.

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)0.010
metaresearch head score (Gemma)0.004
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 score0.267
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.271
GPT teacher head0.571
Teacher spread0.299 · 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

Citations5
Published2014
Admission routes2
Has abstractyes

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