Family Conflicts and Technology Use: The Voices of Grandmothers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Objective Our aim was to understand family conflicts, specifically those involving grandmothers, related to use of new communication technologies. Background Research shows that tension between family members in intergenerational contexts arises in relation to technology. This is especially common when attitudes toward technology differ among family members. Differing opinions around technology use create gaps in skills and perceived competence. Grandparents' voices about the challenges of perpetual connectivity in family settings are absent in the research on technology domestication and mediation. Method To fill this gap, semistructured group interviews were conducted with women in Canada, Colombia, Israel, Italy, Peru, Romania, and Spain. All women were aged 65 years and older, had grandchildren, and used information and communication technology (ICT). Results Grandmothers experienced conflicts when interacting with grandchildren due to ginability to recognize online threats. Asking for help in managing different applications could be a source of family conflicts. Embarrassment and unease is reduced when grandmothers call grandchildren for help, rather than receive assistance from their adult children. Conflictual moments also emerged around the use of ICT at family dinners or other gatherings, with grandmothers showing more tolerance in this context for grandchildren than for their adult children. Conclusion Family conflicts over technology use may differ when involving adult children versus grandchildren. Implications The voices of grandmothers express the importance of permanent and affordable opportunities for people to receive assistance in technology use outside of family contexts.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it