A person‐centered approach to commitment research: Theory, research, and methodology
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.
Bibliographic record
Abstract
Summary There has been a recent increase in the application of person‐centered research strategies in the investigation of workplace commitments. To date, research has focused primarily on the identification, within a population, of subgroups presenting different cross‐sectional or longitudinal configurations of commitment mindsets (affective, normative, and continuance) and/or targets (e.g., organization, occupation, and supervisor), but other applications are possible. In an effort to promote a substantive methodological synergy, we begin by explaining why some aspects of commitment theory are best tested using a person‐centered approach. We then summarize the results of existing research and suggest applications to other research questions. Next, we turn our attention to methodological issues, including strategies for identifying the best profile structure, testing for consistency across samples, time, culture, and so on, and incorporating other variables in the models to test theory regarding profile development, consequences, and change trajectories. We conclude with a discussion of the practical implications of taking a person‐centered approach to the study of commitment as a complement to the more traditional variable‐centered approach. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.004 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it