Profiles of autonomy support and controlling parenting: Mixing the two predicts lower child-perceived autonomy support.
Bibliographic record
Abstract
= 41; 68% mothers) to identify profiles of parenting, using parent-reported autonomy-supportive and controlling behaviors. Parent profiles were then associated with child-perceived parenting and child outcomes, as well as parent-related predictors. A latent profile analysis found four profiles of parents: In most cases, autonomy-supportive and controlling behaviors covaried, most parents simultaneously exhibiting comparable levels of these two parenting dimensions, while only 17% of the parents reported engaging predominantly in autonomy support. This subgroup of parents was perceived by their children to be most autonomy-supportive; their children also showed better school grades and fewer externalizing problems. High-earning and highly educated parents tended to be predominantly autonomy-supportive, while parents whose self-worth was tied to their child's success (i.e., ego-involved parents) tended to resort predominantly to controlling parenting. Finally, we found that when controlling parenting is present, parents and children greatly differ in their assessments of autonomy support, with children perceiving less parental autonomy support than parents' self-reports. These findings shed light on the implications of pairing controlling with autonomy-supportive behaviors within a single parenting style. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".