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Record W2800855957 · doi:10.11575/prism/31878

The Role of Attentional Biases for Conspecific Vocalizations

2018· dissertation· en· W2800855957 on OpenAlexfundno aff
Jennifer Ference

Bibliographic record

VenuePRISM (University of Calgary) · 2018
Typedissertation
Languageen
FieldHealth Professions
TopicInfant Health and Development
Canadian institutionsnot available
FundersAlberta Children's Hospital Research InstituteNational Institutes of HealthAlberta InnovatesKillam Trusts
KeywordsPsychologyCognitive psychologyNeuroscience

Abstract

fetched live from OpenAlex

A bias for speech over non-speech emerges at birth in typically developing (TD) infants and a preference for vocalizations generated from one’s own species (conspecific) emerges by 3 months. These biases and preferences may direct infants to relevant communicative information in their language learning environments, possibly predicting positive linguistic and social development. The first series of studies explored whether a bias for speech (over non-speech) at 6 and 9 months was predictive of language and social behaviors at 12 months. Whether a preference for conspecific vocalizations (over monkey calls) at 9 months was predictive of these same outcomes was also examined. Infants were biased toward speech over non-speech at 6 and 9 months, but preferred monkey calls over speech at 9 months. However, these listening patterns did not predict language or social developmental outcomes. Understanding these patterns of attention and how experimental procedures may influence preferences is important for advancing our understanding of the relationship between attention to speech and early development. The second series of studies reports findings from high-risk (HR) infant siblings of children diagnosed with Autism Spectrum Disorder (ASD), who participated in these same experiments. HR infants are known to have heterogeneous outcomes by age 3, with about half developing typically, while others present with atypical outcomes, including ASD. Given the hypothesized importance of attention to speech on later development, we explored whether HR infants as a group selectively attended to speech and whether such attention was predictive of early language and social behaviors. HR infants were biased toward speech at 6 months; however, by 9 months, they did not differentially attend to speech over non-speech or monkey calls overall. Despite this, increased attention to speech at 9 months predicted better language and fewer autism-like behaviors at 12 months. Therefore, increased attention to conspecifics may indicate typical outcomes for HR infants. Future directions include following both groups of infants to 3 years of age to explore whether selective attention to speech during the first year is predictive of much later developmental outcomes and/or diagnostic status.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.511
Threshold uncertainty score1.000

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 studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.328
Teacher spread0.294 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2018
Admission routes1
Has abstractyes

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