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Record W2102249358 · doi:10.1080/13598139.2010.525341

Motivation within the DMGT 2.0 framework

2010· article· en· W2102249358 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

VenueHigh Ability Studies · 2010
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsVolition (linguistics)Intrapersonal communicationPsychologySet (abstract data type)Action (physics)Process (computing)Identification (biology)SituatedControl (management)Cognitive psychologySocial psychologyComputer scienceInterpersonal communication

Abstract

fetched live from OpenAlex

This article begins with a brief survey of the recent update of the Differentiated Model of Giftedness and Talent (DMGT). The DMGT defines talent development as the transformation of outstanding natural abilities (called gifts) into outstanding knowledge and skills (called talents). Two types of catalysts, intrapersonal and environmental, actively moderate the talent development process. The concept of motivation is situated at the core of the intrapersonal catalysts. Borrowing from action control theory, two goal management sets of processes are differentiated. The first set targets goal‐identification (pre‐decisional) activities, whereas the second set deals with goal‐attainment (post‐decisional) activities. They are labeled ‘motivation’ and ‘volition’ respectively. The article describes these two sets of processes, especially the distinction between goals and motives, as well as some practical impacts of individual differences in motivation and volition.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.327
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.043
GPT teacher head0.338
Teacher spread0.295 · 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