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Record W2802402688 · doi:10.29173/pandpr29356

Acting Slow in a Fast World: A Phenomenological Study of Caring in the Recovery Room

2018· article· en· W2802402688 on OpenAlexvenueno aff
Pia Dreyer, Bente Martinsen, Annelise Norlyk, Anita Haahr

Bibliographic record

VenuePhenomenology & Practice · 2018
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyPsychotherapistCognitive psychology

Abstract

fetched live from OpenAlex

In this paper, we discuss “the slow in the fast” related to care situations in a “fast-track” hospitalsetting were the length of patients’ stay has been reduced significantly. The discussion is basedon a narrative created from observations made in a postoperative care unit where patients areintensively observed and cared for during a very short time span.We found that within the phenomenological notions of lived time, lived space and livedillness, it is possible to create an imaginative space in time – to make a time warp. Despitebeing in a setting where the objective time measure dominates, the nurse can create a rhythmof her own in the room. Thus, acting slow in the quick meeting means that nurse-patientrelationship is characterized by calmness and quietness, the nurse’s engagement in the patient’ssuffering and her help to the patient to endure the present and hold the now.

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)0.009
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 score0.018
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0180.028
Scholarly communication0.0090.010
Open science0.0030.010
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0030.001

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 head0.260
GPT teacher head0.469
Teacher spread0.209 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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