DEVELOPMENTAL TRAJECTORY GROUPS: FACT OR A USEFUL STATISTICAL FICTION?*
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
A rapidly growing literature in criminology and psychology uses a group‐based methodology to identify and analyze developmental trajectories. Some confusion has arisen about the interpretation of this novel statistical model and with it some degree of cautionary commentary. We begin with a discussion of the role of trajectory groups as a statistical device for approximating population differences in developmental trajectories. We then discuss three misconceptions about group‐based trajectory modeling that stem from misunderstandings about the approximating role of trajectory groups: (1) individuals actually belong to a trajectory group, (2) the number of trajectory groups is immutable, and (3) the trajectories of group members follow the group‐level trajectory in lock step. We also point out that groupbased statistical modeling is not bound at the hip to the testing of taxonomic theories, and can just as well be used to test nontaxonomic theories.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.008 | 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