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Record W2892380582 · doi:10.1177/0305735618798031

Revisiting singing proficiency in three-year-olds

2018· article· en· W2892380582 on OpenAlexfundno aff
Helga Rut Guðmundsdóttir

Bibliographic record

VenuePsychology of Music · 2018
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaHáskóli Íslands
KeywordsSingingMelodyPsychologyAudiologyCompetence (human resources)Developmental psychologyAcousticsSocial psychologyMusicalMedicine

Abstract

fetched live from OpenAlex

The present study employed a protocol specially developed for testing toddlers’ singing competence. The protocol was designed to increase responsivity of toddlers during testing. The singing ranges and singing accuracy of three-year-old children were measured using the protocol ( N = 39). A large proportion of the three-year-olds participated in at least one item (89.7%), which is a high rate of participation for this age group, validating the appropriateness of the protocol applied. The most successful test item was the Self-selected song as it elicited the highest response rate of all items (87%). Furthermore, the Self-selected song resulted in more accurate renditions in terms of preservation of melodic contour (85%) and intervals (24%) than another item consisting of a familiar standard song phrase. In ascending pitch glides, 73% of the toddlers lifted their voice above C5 and the highest produced pitch was C6 (two octaves above middle C). Pitch matching accuracy was highly pitch dependent, with middle C as the most accurately matched pitch (53%) and C above middle C the least accurately matched pitch (11%). The findings support previous research that describes three-year-olds as capable singers while contradicting more widely accepted views of three-year-olds having poorly developed singing skills.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.795
Threshold uncertainty score0.387

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.085
GPT teacher head0.357
Teacher spread0.272 · 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 designBench or experimental
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

Citations8
Published2018
Admission routes1
Has abstractyes

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