How Does the Use of ICTs Affect Family Relationships? A Quantitative Approach
Bibliographic record
Abstract
Modern societies are increasingly globalized, where information and communication technologies (ICTs) play a fundamental role in every aspect of daily life: from the social, family, labor, among others. Every day more people who without distinguishing age and gender are seen in the need and desire to have at least one technological device. Objective: To examine the impact of using ICTs in the family relations of the residents of Medellín city. Methodology: exploratory-descriptive research through a quantitative methodological design, a non-probabilistic sampling by criterion was made, where 77 people were selected. Data were collected through a questionnaire type survey with closed questions in a virtual way during 3 Months. Results: among the results, 73.4% of responders suggest that there is no adequate supervision of adults to guide children and adolescents to establish a critical position on these contents. On the other hand, the most valued resources are the mobile device and computer for the possibilities of communication between relatives that are far way and for being means to improve the educational and labor processes. Conclusion: studies around ICTs and their impacts have grown significantly, which it ratifies the importance of the topic. It is imperative that parents stop seeing ICTs as a distant entity, and try to be at the forefront of the uses of the same by children, to generate effective control in the training processes within the family.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 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) | 0.004 | 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".