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Record W2778573035 · doi:10.1037/xge0000334

On the prospect of knowing: Providing solutions can reduce persistence.

2017· article· en· W2778573035 on OpenAlexafffundabout
Evan F. Risko, Michelle Huh, David McLean, Amanda M Ferguson

Bibliographic record

VenueJournal of Experimental Psychology General · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsUniversity of TorontoUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAnagramsPersistence (discontinuity)PsychologyPsycINFOSituational ethicsSocial psychologyMEDLINE

Abstract

fetched live from OpenAlex

Our willingness to persist in problem solving is often held up as a critical component in being successful. Allied against this ability, however, are a number of situational factors that undermine our persistence. In the present investigation, the authors examine 1 such factor-knowing that the answers to a problem are easily accessible. Does having answers to a problem available reduce our willingness to persist in solving it ourselves? Across 4 experiments, participants (university students from a large Canadian University) solved multisolution anagrams and were either provided the answers after giving up (and knew they would receive the answers) or not. Results demonstrated that individuals persisted for less time in the former condition. In addition, participants did not seem to be aware of the effect that answers had on their decisions to quit. Implications for our understanding of the role that access to answers has on persistence across a number of domains (e.g., education, Internet) are discussed. (PsycINFO Database Record

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)0.003
metaresearch head score (Gemma)0.002
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.422
Threshold uncertainty score0.809

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
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 science0.0020.000
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 head0.425
GPT teacher head0.498
Teacher spread0.072 · 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
Published2017
Admission routes3
Has abstractyes

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