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Record W1831784775 · doi:10.1002/ejsp.2038

Self‐determination theory, social media and charitable causes: An in‐depth analysis of autonomous motivation

2015· article· en· W1831784775 on OpenAlex
R. James Ferguson, Jennifer Gutberg, Kaspar Schattke, Michèle Paulin, Nina Jost

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

VenueEuropean Journal of Social Psychology · 2015
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsConcordia University
Fundersnot available
KeywordsPsychologySocial psychologySelf-determination theorySocial mediaIntrinsic motivationContext (archaeology)Online and offlineMeditationTheory of planned behaviorControl (management)AutonomyWorld Wide Web

Abstract

fetched live from OpenAlex

Abstract Using the framework of the self‐determination theory continuum, we investigated the influence of the distinct autonomous and controlled motivational regulations for engaging participants in online and offline support of charitable events for the causes of breast cancer and homeless youth. Participants were exposed online to Facebook event pages appealing to helping others. When the often omitted integrated autonomous regulation was included in the model, it was the strongest predictor of supportive intentions. Without integrated regulation in the model, we would have overestimated the relatively minor influence of controlled introjected regulation. Furthermore, rather than one overall measure of autonomous intrinsic regulation, we assessed the differential influences of three separate dimensions (to experience stimulation, to learn and to accomplish). Intrinsic motivation to experience stimulation had a unique influence on online and offline supportive intentions. Such was not the case for the dimensions of to learn or to accomplish. Follow‐up meditation analyses of self‐reported behaviours confirmed that autonomous integrated and intrinsic to experience stimulation regulations led to stronger intentions to support online behaviours, which, in turn, increased the likelihood of actual online engagement. The findings in a social media context highlight the importance of analysing distinct regulatory styles within the self‐determination theory continuum. Copyright © 2015 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.716
Threshold uncertainty score0.588

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.067
GPT teacher head0.351
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