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Open-Hearted Flesh: Burn Injuries and Interpretation

2022· article· en· W4402507549 on OpenAlexaffvenue
Leah Verburg, Graham McCaffrey, Vincent Gabriel

Bibliographic record

VenueJournal of Applied Hermeneutics · 2022
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsHermeneuticsEmbodied cognitionInterpretation (philosophy)Perspective (graphical)NursingBurn injurySituatedMedicineNursing careEpistemologyPhilosophySurgeryArtComputer science

Abstract

fetched live from OpenAlex

This paper aims to describe the interpretive nature of burn care nursing using an example from the first author’s practice. It asserts how burn injuries are uniquely situated from a hermeneutic perspective as an embodied change that alters the way a burn injured person lives in the world. This paper was written for an assignment in a hermeneutic methodology class, focused on the role of the burns nurse, and further expanded in relation to the hermeneutic significance of burn injuries. It demonstrates the fit of hermeneutics as a way of understanding nursing practice and burn injuries, and serves as a support to the use of hermeneutics in the authors' Master of Nursing thesis project exploring the experiences of burn survivors.

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)0.006
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0080.035
Scholarly communication0.0080.007
Open science0.0010.008
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0040.000

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 head0.019
GPT teacher head0.315
Teacher spread0.296 · 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 designTheoretical or conceptual
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

Citations0
Published2022
Admission routes2
Has abstractyes

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