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Record W2292905734 · doi:10.5430/jnep.v6n4p136

How midwifery students experience learning conditions in labor wards

2016· article· en· W2292905734 on OpenAlexvenueno aff
Anne Brunstad, Tove Giske, Esther Hjälmhult

Bibliographic record

VenueJournal of Nursing Education and Practice · 2016
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsnot available
Fundersnot available
KeywordsDebriefingObstetricsAffect (linguistics)PsychologyNursingMedicineGrounded theoryMedical educationQualitative researchSociology

Abstract

fetched live from OpenAlex

Midwives are responsible for the well-being of women and babies during labor and birth. Learning midwifery is complex and challenging, and how students are welcomed into the labor wards affects learning. This study aimed to identify and explain the conditions that affected midwifery students’ learning in labor wards and their consequences. We used classical grounded theory to analyze longitudinal data from 15 individual and three focus group interviews of 10 postgraduate midwifery students in Norway.The key conditions identified that affect the learning outcomes of midwifery students were related to the students’ relationships with midwives, the students themselves and the learning arena. Tailored assignments from midwives enhanced students’ learning and apprehensive relationships with midwives inhibited learning. Midwives played a key role in facilitating students’ learning by tailoring their learning opportunities and debriefing after challenging incidents and thus smoothed how students’ emotions affect their self-esteem and learning process.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.734
Threshold uncertainty score0.309

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.056
GPT teacher head0.455
Teacher spread0.399 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations23
Published2016
Admission routes1
Has abstractyes

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