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Record W2484079420 · doi:10.1080/02699931.2016.1204989

Measuring emotions during epistemic activities: the Epistemically-Related Emotion Scales

2016· article· en· W2484079420 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCognition & Emotion · 2016
Typearticle
Languageen
FieldPsychology
TopicPsychological and Educational Research Studies
Canadian institutionsMcGill University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyBoredomSurpriseCognitive psychologyCognitionFunction (biology)Value (mathematics)Social psychologyAssertionTask (project management)German

Abstract

fetched live from OpenAlex

Measurement instruments assessing multiple emotions during epistemic activities are largely lacking. We describe the construction and validation of the Epistemically-Related Emotion Scales, which measure surprise, curiosity, enjoyment, confusion, anxiety, frustration, and boredom occurring during epistemic cognitive activities. The instrument was tested in a multinational study of emotions during learning from conflicting texts (N = 438 university students from the United States, Canada, and Germany). The findings document the reliability, internal validity, and external validity of the instrument. A seven-factor model best fit the data, suggesting that epistemically-related emotions should be conceptualised in terms of discrete emotion categories, and the scales showed metric invariance across the North American and German samples. Furthermore, emotion scores changed over time as a function of conflicting task information and related significantly to perceived task value and use of cognitive and metacognitive learning strategies.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.927
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.089
GPT teacher head0.336
Teacher spread0.247 · 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