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Record W4312932053 · doi:10.55975/rdzz9291

Florence Nightingale Foundation Travel Scholarships Part 2: Midwifery in the Netherlands

2020· article· en· W4312932053 on OpenAlexaboutno aff
Sarah Coiffait

Bibliographic record

VenueThe Practising Midwife · 2020
Typearticle
Languageen
FieldNursing
TopicNursing Education, Practice, and Leadership
Canadian institutionsnot available
Fundersnot available
KeywordsMohawkScholarshipMainlandFoundation (evidence)Nurse-MidwivesMainland ChinaNursingPolitical scienceSociologyMedicineMedical educationLibrary scienceHistoryPregnancyLaw

Abstract

fetched live from OpenAlex

The Florence Nightingale Foundation provides scholarships for nurses and midwives in three categories: leadership, research and travel. This year the foundation has awarded three midwives a travel scholarship enabling them to study best practice and innovation away from home. This series will include reports from all three scholars who have travelled to mainland Europe, Canada, Africa and Australia. The projects include learning about how student midwives are involved in continuity of care in the Netherlands, midwives and mothers in a First Nations Mohawk community and women in global health leadership. In this second article, Sarah Coiffait reports her experience of a Dutch summer school for midwives.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.114
Threshold uncertainty score0.382

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0040.001
Open science0.0010.004
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.1140.016

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 head0.088
GPT teacher head0.330
Teacher spread0.242 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2020
Admission routes1
Has abstractyes

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