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Record W2606816334 · doi:10.1002/bdm.2018

Evaluating Effort: Influences of Evaluation Mode on Judgments of Task‐specific Efforts

2017· article· en· W2606816334 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.

Bibliographic record

VenueJournal of Behavioral Decision Making · 2017
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPsychologyStimulus (psychology)Cognitive psychologyCognitionSocial psychologyNeuroscience

Abstract

fetched live from OpenAlex

Abstract The claim that humans adapt their actions in ways that avoid effortful processing (whether cognitive or physical) is a staple of various theories of human behavior. Although much work has been carried out focusing on the determinants of such behaviors, less attention has been given to how individuals evaluate effort. In the current set of experiments, we utilized the general evaluability theory to examine the evaluability of effort by examining subjective value functions across different evaluation modes. Individuals judged the anticipated effort of four task‐specific efforts indexed by stimulus rotation, items to be remembered, weight to be lifted, and stimulus degradation across joint (i.e., judged comparatively) and single evaluation modes (i.e., judged in isolation). General evaluability theory hypothesizes that highly evaluable attributes should be consistently evaluated (i.e., demonstrate similar subjective value functions) between the two modes. Across six experiments, we demonstrate that the perceived effort associated with items to be remembered, weight to be lifted, and stimulus degradation can be considered relatively evaluable, while the effort associated with stimulus rotation may be relatively inevaluable. Results are discussed within the context of subjective evaluation, internal reference information, and strategy selection. In addition, methodological implications of evaluation modes are considered. Copyright © 2017 John Wiley & Sons, Ltd.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.910
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.291
GPT teacher head0.575
Teacher spread0.284 · 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