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Record W2099863825 · doi:10.1177/0894318405274809

Feeling Respected-Not Respected: The Embedded Artist in Parse Method Research

2005· review· en· W2099863825 on OpenAlexaff
Gail J. Mitchell, Nancy Davis Halifax

Bibliographic record

VenueNursing Science Quarterly · 2005
Typereview
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsUniversity Health NetworkSunnybrook Health Science CentreYork University
Fundersnot available
KeywordsFeelingMeaning (existential)Plan (archaeology)ParsingOrder (exchange)Complement (music)PsychologyAestheticsComputer scienceArtSocial psychologyArtificial intelligencePsychotherapistHistory

Abstract

fetched live from OpenAlex

The purpose of this column is to present the plan of a research project involving researchers, artists, and research participants. The planned research project will explore with the Parse method eight universal lived experiences important to persons in community. It is anticipated that art works will complement story and text in order to enhance understanding. The authors here present the first attempt of including an embedded artist with Parse method involving one participant who spoke about her experience of feeling respected-not respected. Researcher text and artist works are shown to enhance meaning and understanding.

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)0.072
metaresearch head score (Gemma)0.065
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.072
Threshold uncertainty score0.382

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0720.065
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.006
Science and technology studies0.0030.016
Scholarly communication0.0100.011
Open science0.0020.006
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.217
GPT teacher head0.562
Teacher spread0.345 · 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
GenreReview

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

Citations11
Published2005
Admission routes1
Has abstractyes

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