Investigating the Effects of Instagram on Creating Body Image 14-30 Years Old Female and Male Users in Tehran Province Using Littleton Body Image Questionnaire
Bibliographic record
Abstract
This study was an attempt to examine the effects of Instagram on creating body image 14-30 years old female and male users in Tehran province by using Littleton body image questionnaire. The participants of the study were one hundred and twenty Iranian men and women in Tehran province. This study used two groups (total N = 120) to explore relations between Instagram social media use and body image in early adolescent girls and boys (ages 14-30). The participants were given Littleton questionnaire. Two tests were run to analyze the results of the study. Kruskal-wallis test for data analysis were used to examine the research question about body image. Another test was single sample t-test to evaluate Dissatisfaction and embarrassment of the person to hide the perceived defects. So the finding revealed that Instagram does not affect the women and men worries about their appearance in social performance.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".