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Record W4247567427 · doi:10.31234/osf.io/y3cr9

A Model of Listening Engagement (MoLE)

2019· preprint· en· W4247567427 on OpenAlexaff
Björn Herrmann, Ingrid S. Johnsrude

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicCommunication in Education and Healthcare
Canadian institutionsUniversity of TorontoWestern University
Fundersnot available
KeywordsActive listeningDisengagement theoryPsychologyBoredomInformational listeningAppreciative listeningReflective listeningCognitive psychologyCognitionSocial psychologyDevelopmental psychologyListening comprehensionCommunication

Abstract

fetched live from OpenAlex

Hearing impairment in older adulthood puts people at risk of communication difficulties, disengagement from listening, and social withdrawal. Here, we develop a model of listening engagement (MoLE) that provides a conceptual foundation to understand when people engage in listening and why some people disengage. We use the term “listening engagement” to describe the recruitment of executive and other cognitive resources in the service of a valued communication goal. Listening engagement, listening motivation, and listening experiences are closely interconnected: motivation and other factors determine the degree to which resources are recruited during listening, which in turn influences subjective listening experiences such as enjoyment, effort, frustration, and boredom. We anticipate that this model will help researchers assess more accurately whether a person with hearing difficulties is at risk of disengagement and social withdrawal. It is further useful to more comprehensively characterize a person’s listening experiences in laboratory settings when rich, engaging stimulus materials, such as spoken stories, are used. We hope this model will allow new questions in applied and basic hearing science and auditory cognitive neuroscience to be asked and answered.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.871
Threshold uncertainty score0.995

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.277
GPT teacher head0.482
Teacher spread0.205 · 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 designTheoretical or conceptual
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

Citations21
Published2019
Admission routes1
Has abstractyes

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