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Record W2792585817 · doi:10.1177/0894318418755730

The Living Experience of Suffering: A Parse Method Study

2018· article· en· W2792585817 on OpenAlexaff
Judith D. Hart

Bibliographic record

VenueNursing Science Quarterly · 2018
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsMinistry of Health and Long Term Care
Fundersnot available
KeywordsRelation (database)ParsingPsychologyIndependent livingActivities of daily livingGerontologyMedicinePsychiatryComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

The purpose of this study was to investigate the humanuniverse living experience of suffering. The Parse method was used to answer the question: What is the structure of the living experience of suffering? The participants were 10 adults living in the community. The finding of the study, the structure of the living experience of suffering, was found to be as follows: Suffering is anguishing desolation with varied alliances arising with envisioning anew. The living experience of suffering is discussed in relation to the principles of the humanbecoming paradigm and in relation to further research inquiries.

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)0.010
metaresearch head score (Gemma)0.015
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 score0.010
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0080.007
Scholarly communication0.0040.003
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.042
GPT teacher head0.487
Teacher spread0.445 · 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

Citations9
Published2018
Admission routes1
Has abstractyes

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