Person-Centered Methodologies in the Organizational Sciences
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
The 2011 Organizational Research Methods Feature Topic on latent class procedures has helped to establish person-centered analyses as a method of choice in the organizational sciences. This establishment has contributed to the generation of substantive-methodological synergies leading to a better understanding of a variety of organizational phenomena and to an improvement in research methodologies. The present Feature Topic aims to provide a user-friendly introduction to these new methodological developments for applied organizational researchers. Organized around a presentation of the typological, prototypical, and methodologically exploratory nature of person-centered analyses, this introductory article introduces seven contributions aiming to: (a) clarify the meaning, advantages, and applications of person-centered analyses; (b) illustrate emerging prototypical and longitudinal cluster analytic approaches; (c) introduce researchers to multilevel person-centered analyses as well as to auxiliary approaches that will drastically increase the scope of application of these methods; and (d) describe the application of these methods for confirmatory purposes.
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 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 | 0.077 | 0.096 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.013 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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