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Record W2002290375 · doi:10.1177/089033440101700107

Women’s Experiences Breastfeeding in Public Places

2001· article· en· W2002290375 on OpenAlexaff
Judy Sheeshka, Beth K. Potter, Emilie Norrie, Ruta Valaitis, Gerald R. Adams, Leon Kuczynski

Bibliographic record

VenueJournal of Human Lactation · 2001
Typearticle
Languageen
FieldMedicine
TopicBreastfeeding Practices and Influences
Canadian institutionsMcMaster UniversityInstitute for Christian StudiesWestern UniversityUniversity of Guelph
Fundersnot available
KeywordsBreastfeedingMedicinePsychologyPerceptionBreast feedingFormula feedingNursingDemographyPediatricsSociology

Abstract

fetched live from OpenAlex

This two-part field study compared researchers' recorded observations to mothers' perceptions of attention they received while publicly breastfeeding. In part 1, four breastfeeding and four bottle-feeding mothers each made eight restaurant visits. On average, there were more neutral looks from customers (P = .01) during breastfeeding visits, but no differences in the amount of overtly negative or positive attention given during breastfeeding versus bottle feeding. In part 2, four breastfeeding mothers made a total of 24 visits to shopping malls. There were more neutral looks given while mothers were breastfeeding and more smiles and comments while they were not feeding, but no difference in total amount of attention received. Breastfeeding mothers acknowledged they had anticipated some undesirable attention but instead received little attention. Nevertheless, they felt "vulnerable" nursing in public. Certain proactive behaviors and personal attributes as well as support from other women enabled them to breastfeed successfully in public.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.046
GPT teacher head0.325
Teacher spread0.279 · 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

Citations61
Published2001
Admission routes1
Has abstractyes

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