"I communicate with my children in the game": Mediated Intergenerational Family Relationships through a Social Networking Game
Bibliographic record
Abstract
How might social networking game playing affect intergenerational family relationships? Motivated by this important research question, we examined game-based communication patterns among family members. We investigated QQ Farm, one of the most popular online games available on a Chinese social networking site. Participatory observations and semi-structured interviews were conducted with sixteen pairs of Chinese parents and their adult children. Our analysis shows that game-based communication does not replace face-to-face or phone-based communication. Rather, it adds a new layer to the existing family communication patterns, which enriches the other forms of family communication and provides a new means for intergenerational family members to stay in touch. Game playing provides a light-weighted and relaxed environment for intergenerational family members to stay connected. It serves as an “I’m safe and well” message board for family members to stay connected without imposing an undue burden for anyone. Moreover, game playing implicitly conveys caring messages to family members. It becomes a new communicative topic to promote the mutual shaping of online and offline intergenerational family communication.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".