Commentary: On the importance of looking at nonlinearity and developmental effects – a reflection on Flom et al. (2017)
Bibliographic record
Abstract
By examining both linear and curvilinear associations between mental development and activity level, the study by Flom et al. (Journal of Child Psychology and Psychiatry, 2017) highlights the importance of going beyond linear associations in psychological fields of research. Results from Flom et al. (Journal of Child Psychology and Psychiatry, 2017) also raise interesting questions for future research. First, studies should look at variables that may explain the associations between activity level and mental development, such as self-regulation and attention. Second, longitudinal changes in the strength of the association between activity level and mental development should be examined to determine when this association is at its strongest. Finally, longitudinal research looking at bidirectional effects is needed to confirm the direction of the associations between activity level and mental development. Answers to these questions will allow the identification of the best targets and developmental periods for interventions to take place.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.030 | 0.183 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.006 | 0.013 |
| Open science | 0.013 | 0.005 |
| Research integrity | 0.062 | 0.081 |
| Insufficient payload (model declined to judge) | 0.011 | 0.010 |
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 source (direct Gemma or distilled Codex), 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".