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Record W4288435628 · doi:10.1080/00405841.2022.2107808

“Keep calm and earn more points”: What research says about token economy systems

2022· article· en· W4288435628 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.

Bibliographic record

VenueTheory Into Practice · 2022
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsUniversité du Québec en OutaouaisUniversity of OttawaUniversité de MontréalUniversité de Sherbrooke
Fundersnot available
KeywordsToken economyScope (computer science)Security tokenPosition (finance)Public relationsBusinessMarketingPsychologyEconomicsPolitical scienceComputer scienceSocial psychologyComputer security

Abstract

fetched live from OpenAlex

The use of reward systems is common in education, particularly at the primary school level. Indeed, there are very few classes in primary schools in which such systems are not implemented. Token economy are used to encourage students to adopt appropriate target social and academic behaviors. However, consensus on their effectiveness is lacking. It is beyond the scope of this article to determine whether token economy systems actually achieve their intended purpose. This article does provide important insights into their origins and offers an up-to-date overview of the research on their effects, which serve as a basis for recommendations to educators and administrators who may need to take a position on their use.

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)0.009
metaresearch head score (Gemma)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.807
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0140.001

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 head0.046
GPT teacher head0.392
Teacher spread0.345 · 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