Information and Communication Technologies Influence on Family Relationship
Bibliographic record
Abstract
BACKGROUND: Information and Communication Technologies (ICTs) have affected various dimensions of modern societies, modifying even economic, politic, social and cultural structures. Therefore, it cannot be ignored the positive impacts according to social knowledge appropriation, but even in proper dimensions of social and family relationship, where ICTs usage has been compared with narcotic additions.OBJECTIVE: Explore how the use of ICTs have impacted the family interaction in Medellin city, 2016.METHODOLOGY: The study was carried out through an exploratory qualitative and a convenience sampling research. A self-administered instrument supported by a Likert scale was used, applied to a group of residents of Medellin city.RESULTS: It is observed that although ICTs have enabled a large flow of information that reinforces the nuclear family, particularly children, also have caused a detriment in communication processes and family life, generating sensations that lead to family members perceive a “distant relationship”, which goes against the current family concept.CONCLUSION: It is pertinent to encourage further researches to evaluate the impact of ICTs on the relationship processes from a qualitative vision and through longitudinal studies, and explore how new technologies have redefined the concepts of family life in modern societies.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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".