Bibliographic record
Abstract
Les recherches de psychologie industrielle/organisationnelle (I/O) sur les objectifs et l’autorégulation ont prospéré durant les trois dernières décennies. Initiés par le travail fécond de Locke, Latham et de leurs collègues qui ont souligné l’influence positive d’objectifs elairs et sollicitants sur les performances, de nombreux courants de recherche sont apparus pour étudier à la fois les déterminants et les conséquences des objectifs et des processus d’autorégulation sur les conduites et les variables dépendantes relatives au travail (voir par exemple ; pour une revue de questions). constatent que si les chercheurs en organisations ont tenté d’évaluer la validité externe et critérielle, ils se sont moins intéressés à la validité interne et de construction des variables‐clés et de concepts tels que les objectifs, la rétroaction, la divergence et l’efficacité personnelle. Dans le même ordre d’idées, Vancouver et Day (2004) concluent que les validations des interventions I/O fondées sur la perspective objectif/autorégulation détectent généralement des effcts positifs, mais que ces travaux sont insuffisants pour déterminer les dimensions spécifiques du processus objectif/autorégulation qui sont en rapport avec l’amélioration de la performance. Dans ce court article, j’aborde ces problèmes concemant la recherche sur les objectifs et l’autorégulation d’un triple point de vue: le progrès scientifique, les applications et les buts des investigations I/O. Over the past three decades, industrial/organisational (I/O) research on goals and self‐regulation has flourished. Beginning with the seminal work by Locke, Latham, and their colleagues showing the positive influence of difficult and specific goals on task performance, multiple streams of research have emerged to investigate both the determinants and consequences of goals and self‐regulation processes on work‐related behaviors and outcomes (see, e.g. ; , for reviews). In a review of this work, ) suggest that although organisational researchers have sought evidence for external and criterion‐related validity, less attention has been given to the construct and internal validity of key variables and concepts, such as goals, self‐efficacy, feedback, discrepancy, and self‐efficacy. In a related vein, ) conclude that although I/O intervention studies based on the goal/self‐regulation perspective show generally positive effects, such studies are insufficient for understanding how specific aspects of the goal/self‐regulation process relate to enhanced performance. In this short note, I consider these concerns about goal/self‐regulation research in I/O psychology from three perspectives: (1) scientific progress, (2) applications, and (3) the goals of I/O research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".