The Role of Family Disintegration in Piracy of Electronic Games “A Field Study”
Bibliographic record
Abstract
Purpose: Recognizing the technological effects of family disintegration. Method: Human field: a sample of the dangerous electronic games players, including "4" players who are still alive, and "5" players who committed suicide. Methods and Tools: The Case study method, Ethnographic method, Descriptive approach, and Interview. The research type is Analytic, and the theoretical framework is Postmodernism Theory. Originality: The researcher tries to provide a comprehensive view of how electronic games piracy on their players and pushes them to suicide, in the presence of the family disintegration element. Findings: family disintegration was the main reason for children’s addiction to electronic games. Thus, electronic games were like escaping from reality and living in imagination, and spending free time. Also, electronic games were a means that absorbed the negative charge and feelings of anger among the children instead of the family. There are many types of piracy on players: (programming for the mind, charging with negative thoughts, threatening to kill parents, an emotional challenge to the teenager, blackmail and intimidation, or with talismans). Conclusion: a person can control another, to the extent that this other person allows this person to control him. Do not allow a game administrator to control you, activate Cybersecurity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".