THE CONTRIBUTION OF THE HUMAN DEVELOPMENT THEORY FOR THE EDUCATION AND MENTAL HEALTH OF THE CHILD
Bibliographic record
Abstract
According to the ecosystemic model of Bronfenbrenner (1979), the development of an individual is part of an environmental system that is complex and in interaction, built around a microsystem and being dinamic in relation to a macrosystem. This article presents and questions the ecological theory of human development and wants to illustrate the applications of the Bronfenbrenner model in the field of today’s education and in the field of mental health of the child and adult.The social ecology theory takes as a postulate that the development and behavior of the individual are the result of continuous influences between the individual and his environment. If we are not careful, a child who has potential, can develop behavioral problems or problems of adaptation in an environment with high-level risk factors. After having quickly presented the ecological approaches in sociology and psychology from 1920 to 1950, two cases of schools and pedagogical projects based on self-esteem and creativity will be illustrated: one in Luxembourg, Europe, and the other in the USA, in Washington.They show how the mental health of young children may affect the learning process. In the field of public mental health, the declination of the Bronfenbrenner theory is relevant: the Ottawa Charter, WHO, 1986, has been supporting, for 30 years, the creation of favorable environments that determine good physical and mental health of the population.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.016 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".