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Record W4396911057 · doi:10.26689/ijgpn.v1i1.5047

A Situational Analysis of the Discourse of Mothers Who Have Chosen an Alternative to Exclusive Breastfeeding: Challenges in Nursing Practice

2023· article· en· W4396911057 on OpenAlexaff
Sandrine Vallée‐Ouimet, Monique Benoît, Pierre Pariseau‐Legault

Bibliographic record

VenueInternational journal of general practice nursing. · 2023
Typearticle
Languageen
FieldMedicine
TopicBreastfeeding Practices and Influences
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsBreastfeedingNegotiationSituational ethicsNursingNorm (philosophy)PsychologyQualitative researchHealth careSet (abstract data type)MedicineSocial psychologySociologyPediatricsPolitical science

Abstract

fetched live from OpenAlex

The health benefits of breastfeeding for infants have been established by numerous scientific studies. However, mothers who opt for alternatives to exclusive breastfeeding may feel guilty or that they have failed. This issue raises the importance of understanding the experiences of these mothers, who live on the fringes of public policies and healthcare practices that currently favor exclusive breastfeeding. This qualitative research presents a situational analysis of the experiences of nine mothers who chose alternatives to breastfeeding and interviewed in the form of semi-structured interviews. The results describe the decision-making processes involved in choosing an alternative to breastfeeding, situate this choice within a set of care measures that are culturally congruent with breastfeeding, and position this choice in relation to the social norm of breastfeeding. The discussion presents the processes of negotiation and resistance mobilized by the mothers concerning the different norms related to breastfeeding.

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)0.014
metaresearch head score (Gemma)0.025
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 score0.014
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0110.013
Scholarly communication0.0070.006
Open science0.0010.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.054
GPT teacher head0.430
Teacher spread0.376 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueInternational journal of general practice nursing.→Same topicBreastfeeding Practices and Influences→French-language works237,207→