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Record W4392303823 · doi:10.1093/deafed/enad034

Family-Centered Early Intervention Deaf/Hard of Hearing (FCEI-DHH): Methods

2024· article· en· W4392303823 on OpenAlexaff
Sheila Moodie, Mary Pat Moeller, Amy Szarkowski, Elaine R. Silliman, Trudy Smith, Bianca C Birdsey, Gwen Carr, Arlene Stredler-Brown, Christine Yoshinaga‐Itano, Daniel Holzinger

Bibliographic record

VenueThe Journal of Deaf Studies and Deaf Education · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsWestern University
FundersU.S. Department of Health and Human Services
KeywordsPsychologyIntervention (counseling)Set (abstract data type)Deaf educationDevelopmental psychologyLinguisticsComputer scienceSign languagePsychiatry

Abstract

fetched live from OpenAlex

This is the fourth article in a series of eight that comprise a special issue on family-centered early intervention (FCEI) for children who are deaf or hard of hearing (DHH) and their families, FCEI-DHH. This article describes the co-production team and the consensus review method used to direct the creation of the 10 Principles described in this special issue. Co-production is increasingly being used to produce evidence that is useful, usable, and used. A draft set of 10 Principles for FCEI-DHH and associated Tables of recommended behaviors were developed using the knowledge creation process. Principles were refined through two rounds of eDelphi review. Results for each round were analyzed using measures of overall group agreement and measures that indicated the extent to which the group members agreed with each other. After Round 2, with strong agreement and low to moderate variation in extent of agreement, consensus was obtained for the 10 Principles for FCEI-DHH presented in this special issue. This work can be used to enhance evolution of FCEI-DHH program/services and systems world-wide and adds to knowledge in improvement science.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.862
Threshold uncertainty score0.244

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.282
GPT teacher head0.575
Teacher spread0.293 · 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 designOther design
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

Citations10
Published2024
Admission routes1
Has abstractyes

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