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Record W3012056839 · doi:10.1055/s-0040-1701683

A Conceptual Framework of Social Communication: Clinical Applications to Pediatric Traumatic Brain Injury

2020· article· en· W3012056839 on OpenAlexaff
Catherine Wiseman‐Hakes, Lisa Kakonge, Meghan E. Doherty, Miriam H. Beauchamp

Bibliographic record

VenueSeminars in Speech and Language · 2020
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversité de MontréalHolland Bloorview Kids Rehabilitation HospitalMcMaster UniversityToronto Rehabilitation Institute
Fundersnot available
KeywordsSocial communicationPsychological interventionPerspective (graphical)Intervention (counseling)Traumatic brain injuryPsychologySocial isolationDevelopmental psychologyPsychiatryComputer science

Abstract

fetched live from OpenAlex

Social communication impairments are common following pediatric traumatic brain injury (TBI) and can lead to social isolation, and poor social outcomes. Social communication has been documented as a persistent area of need in terms of proper assessment and intervention; however, this is not consistently addressed in clinical practice. While there is a body of evidence regarding social communication impairments and pediatric TBI, this area is not yet fully understood and remains underrecognized. To meet this gap, we provide a conceptual framework of social communication from a neurodevelopmental perspective, which can be applied to better understand the social communication impairments associated with pediatric TBI. We propose a general model of social communication with component constructs and consideration of internal factors such as sex and gender. These can inform considerations, clinical applications, and future research in assessment and evidence-based interventions within the domain of social communication.

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)0.007
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0030.017
Scholarly communication0.0050.006
Open science0.0020.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.073
GPT teacher head0.424
Teacher spread0.351 · 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 designTheoretical or conceptual
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

Citations15
Published2020
Admission routes1
Has abstractyes

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