HOLISTIC DEVELOPMENT OF ADOLESCENTS FOR SOCIAL INTELLIGENCE, EMOTIONAL MATURITY AND SPIRITUAL PERSONALITY FOR NATION BUILDING
Bibliographic record
Abstract
Over 225 million adolescents reside in India which is greater than the total population of Germany, United Kingdom, and Canada put together. It is imperative that this immense human potential be given an enabled environment, empowered and effectively mobilized for the holistic development of adolescents and consequently the nation. To understand the complexities of young people, most of which arise from their very state of transition, this study assesses the relationship between emotional maturity (EM), social intelligence (SI) and spiritual personality (SP) among 100 randomly selected adolescent students from Jodhpur district (50 boys and 50 girls) and aged between 16 and 19. Data was collected using the Emotional Maturity Scale (EMS), Social Intelligence Scale (SIS) and Spiritual Personality Inventory (SPI) and analyzed using t-test, product moment correlation coefficient and multiple regression tools. Results obtained indicated that there is a significant difference in the three groups of adolescents - higher , middle and lower groups, based on SI, EM and SP scores and gender differences in relation to their emotional maturity, social intelligence and the spiritual personality. Regression analysis showed a contribution of SI and EM to SP, suggesting that individuals with more SI, EM, and SP, can holistically contribute to national development. Keywords: Holistic Development, Adolescent, Social intelligence, Emotional Maturity, Spiritual Personality
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".