Notice bibliographique
Résumé
Goal pursuit is ubiquitous in everyday life, which has subsequently led to the proliferation of a multitude of theories and perspectives on what constitutes successful goal pursuit. While all of this work is indeed a testament to the centrality of goals in the context of motivational psychology, the problem, however, is that researchers often focus on only one particular theory while often ignoring other (possibly competing or overlapping) ideas. To address this concern, we conducted a prospective longitudinal study in order to determine which factors best predict goal progress over time. Participants (n = 799) were asked to set three week-long goals, as well as completed an extensive battery of measures, including 14 individual difference measures assessed at the between-person level and seven goal-specific measures assessed at the within-person level. Participants then reported how much progress they made on each of their goals at the end of the week. In keeping with best measurement practices, we first examined the validity of all self-report measures used in the study. Results indicate that the majority (92%) of individual difference measures demonstrated good internal consistency, although only a subset (71%) provided some evidence during more rigorous tests of validity. Upon examining the potential for overlapping constructs, three latent factors emerged providing evidence of substantial jangle-fallacies within the goal pursuit literature. Finally, using Bayesian model comparison we examined the extent to which these constructs predicted goal progress. Results indicate that people were more likely to make progress on the goals that they are committed to, have plans for, or that are more autonomous compared to their other goals. Additionally, we found that people who had specific plans for pursuing their goals, were more intrinsically oriented, experienced more competence in their daily life, experienced less frustration for their need for autonomy, and were able to re-engage in goals following failure made more progress on their goals compared to other people. The discussion focuses on implications of the present research on the field of self-regulation and goal pursuit, as well as measurement practices and theory development within social and personality psychology more broadly.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».