Self-esteem, empathy and introversion among adolescent readers
Bibliographic record
Abstract
Aim: This study is aimed to investigate the levels of self-esteem, empathy and introversion in adolescent readers based on their levels of reading. Self-esteem is quite simply one’s attitude toward oneself (Rosenberg, 1965). Empathy can be defined as the act of coming to experience the world as you think someone else does (Bloom, 2016). Introversion refers to a personality type in which there is an orientation towards the internal private world of one’s self and one’s own inner thoughts and feelings, rather than towards the outer world of people and things (American Psychological Association [APA]). Individuals belonging to this category are usually quiet, reserved and shy. Adolescence refers to the period of human development that starts with puberty (10-12 years) and lasts till maturation (approximately 19 years). Method: This study has been conducted on 120 participants belonging to adolescent age group (09-19 years) through purposive sampling. The tools for data collection used in the study are Rosenberg Self-esteem Scale (Morris Rosenberg, 1965), Toronto Empathy Questionnaire (Spreng et.al, 2009) and Introversion Scale (McCroskey). Data is analyzed using SPSS by the application of Kruskal Wallis Test and Post-hoc analysis. Results: The results indicate significant difference in the levels of self-esteem, empathy and introversion among adolescent readers varying on their reading level. That is, individuals with high levels of reading show higher levels of self-esteem, empathy and introversion compared to their counterparts.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".