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The Kangaroo Program at a Brazilian maternity hospital: the preterm/low-weight babies’ health-care under examination

2011· article· en· W2147749784 on OpenAlexaff
Renata Meira Véras, Martha Traverso-Yépez

Bibliographic record

VenueNursing Inquiry · 2011
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMaternity careMedicineLow birth weightObstetricsNursingHealth careFamily medicinePregnancyPolitical science

Abstract

fetched live from OpenAlex

The Kangaroo Program, originally developed in Colombia, was adopted as a public policy by the Brazilian Unified Health System (SUS) in 2000, in an effort to improve maternal and infant health in the country. This article aims to examine the Kangaroo Program as it is practiced and carried out at a maternity hospital in the northeastern Brazilian region. Through an institutional ethnographic approach, research demonstrates that the Kangaroo Program has been effective in saving lives and improving some of the infants' health outcomes. However, research also demonstrates that: (i) the socioeconomic profile of mothers in the Kangaroo Program, (ii) conflicting relationships between healthcare workers and users, and (iii) lack of socioeconomic and emotional support are impairing the adequate implementation of the program. Due to the low literacy level of most of these mothers, institutional power is used as a form of social control to keep mothers uninformed about the possibility of leaving the maternity wards. In a two-tier health system, this controlling behavior is part of existing social inequities, as the Kangaroo Program is a choice in the private health system but tends to be mandatory at SUS maternity hospitals across Brazil.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.921
Threshold uncertainty score0.660

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
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 head0.033
GPT teacher head0.310
Teacher spread0.277 · 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 designObservational
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

Citations9
Published2011
Admission routes1
Has abstractyes

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