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Record W4315817609 · doi:10.53841/bpssepr.2017.13.1.94

The 6th International Conference on Self-Determination Theory: A review and emerging themes

2017· review· en· W4315817609 on OpenAlexaboutno aff
Alex Hodge

Bibliographic record

VenueSport & Exercise Psychology Review · 2017
Typereview
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsnot available
Fundersnot available
KeywordsDeci-Self-determination theoryPsychological interventionPsychologyPolitical scienceSociology

Abstract

fetched live from OpenAlex

The 6th International Conference on Self-Determination Theory (SDT: Deci & Ryan, 1985, 2000) was held from 2–5 June, 2016, in Victoria, British Colombia, Canada. The conference was organised by the Universities of Victoria, Alberta and Saskatchewan, and attracted more than 400 attendees, from varying academic disciplines. This review highlights major themes of the conference, including: 1) challenges to the triad of basic psychological needs; 2) a focus on further examination of need thwarting, frustration and satisfaction; and 3) practical applications and interventions using SDT. All of these themes are tied to sport, exercise science and behaviour management. Future directions for research, both applying and advancing SDT, are discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0060.008
Science and technology studies0.0010.003
Scholarly communication0.0050.005
Open science0.0020.003
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0060.002

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 head0.121
GPT teacher head0.464
Teacher spread0.343 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations4
Published2017
Admission routes1
Has abstractyes

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