The Influence of Internet Media on Young Adult Development
Bibliographic record
Abstract
The study examines from a Christian worldview how free will, regarded as God's greatest gift, is now being shaped by human influence. New treatment methods become essential to adapt to the media-changing world and help with developmental delays. The purpose of this qualitative grounded theory lite study was to explore Internet media’s influence on young adults in Quebec, Canada. Data on Internet media demographics, social behavior, identity, influence, emotional self-regulation, and moral decision-making were collected by conducting twelve semi-structured, audio-recorded interviews with young adults in Quebec. The responses were coded into six primary themes, with an intercoder conducting a cross-verification to enhance the validity of the coding process. The interviews revolved around the three research questions on how the experiences of young adults with heavy internet media use relate to social behavior, identity, and self-regulation developmental delays. Participants were 18 to 32 years old, with no struggles with identity, previous diagnosis, or trauma. The results showed that all twelve participants were heavy media users and eleven of them used it for entertainment. Some results supported it while others refuted previous research on media influence on development. The implications of the data closed the gap regarding the extent Internet media influences social (identity and social behavior) and socio-emotional (self-regulation of emotions) development, by adding qualitative data to quantitative numbers. Understanding these relationships and their signs will better prepare those in a helping role (counselors, therapists, and all caregivers) to monitor and intervene.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".