Grannies on the Net: Grandmothers’ Experiences of Facebook in Family Communication
Bibliographic record
Abstract
Despite ageist stereotypes about older people’s abilities to engage with information and communication technologies, grandparents are increasingly engaged with digital media. Grandmothers, in particular, are primarily responsible for using of web-based services to communicate with their children and grandchildren (Quadrello et al., 2005). Photos and news from children and grandchildren, especially grandbabies, act as important incentives for grandparents to go online. The purpose of the study, therefore, was to investigate how grandmothers use Facebook to facilitate family communication with children and grandchildren who move far away from home. Semi-structured interviews were conducted with grandmothers living in Romania and Canada, having a Facebook account and relevant family members (children or grandchildren) far from home. Three themes emerged from the data indicating: 1) the tendency to switch between different platforms to facilitate family communication; 2) the relative passive use of Facebook, focusing on photos and quotations as content that trigger emotions; 3) that Facebook usage is influenced by social norms around decency and privacy. Findings suggest that family relationships play a central role in grandmothers’ motivations and behaviours surrounding Facebook use.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".