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Record W3013517059 · doi:10.1177/0844562120914424

Promoting First Relationships®: Implementing a Home Visiting Research Program in Two American Indian Communities

2020· article· en· W3013517059 on OpenAlexvenueno aff
Monica L. Oxford, Cathryn Booth‐LaForce, Abigail Echo‐Hawk, Odile Madesclaire, Lorilynn Parrish, Mylene Widner, Anthippy Petras, Teresa Abrahamson-Richards, Katie Nelson, Dedra Buchwald

Bibliographic record

VenueCanadian Journal of Nursing Research · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
FundersNational Institute on Minority Health and Health DisparitiesNational Institute of Nursing Research
KeywordsReservationParticipatory action researchFidelityNative americanFocus groupCitizen journalismCommunity-based participatory researchMedical educationCulturally appropriatePublic relationsPsychologyNursingSociologyMedicinePolitical scienceEngineeringGerontology

Abstract

fetched live from OpenAlex

BACKGROUND: Few, if any, home visiting programs for children under the age of three have been culturally adapted for American Indian reservation settings. We recently adapted one such program: Promoting First Relationships®. OBJECTIVES: To culturally adapt Promoting First Relationships® while maintaining program fidelity, we used a community-based participatory approach to elicit input from two American Indian partners. METHODS: University-based researchers, reservation-based Native project staff, and Native tribal liaisons conducted collaborative meetings, conference calls, and focus groups to adapt Promoting First Relationships® to reflect local community needs and values. LESSONS LEARNED: Working closely with onsite Native project staff, being flexible and open to suggestions, and attending to the logistical needs of the community are imperative to developing and implementing adaptations. CONCLUSIONS: Several adaptations were made based on the collaboration between researchers and Native project staff. Collaboration is critical for adapting programs so they can be tested in ways that respect both American Indian culture and research needs.

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)0.021
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.283
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0210.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0210.002
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.003
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 head0.240
GPT teacher head0.510
Teacher spread0.270 · 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.

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

Citations12
Published2020
Admission routes1
Has abstractyes

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