« T’es un vrai … si … » : quand les seniors aiment leur ville au sein de groupes Facebook
Bibliographic record
Abstract
In 2014, French and Belgian Facebook members witnessed the flourishing of numerous Facebook groups dedicated to their town or village that shared the same rallying cry, “You’re a real … if …” This trend spread like wildfire, to the extent that more than 160 towns/villages now have an active page on the social network. Seniors are among the most active members of these groups. In this context, the general objective of our study consisted of identifying the mechanisms through which these pages participate in building a real geo-cultural community in which the oldest Facebook members play a central role. To do so, we performed a content analysis of the 842 posts and 5,314 comments written between December 5, 2014 and January 5, 2015 in the groups representing the cities of Hannut and Jodoigne (Belgium) as well as Fourmies and Harnes (France). Our study concerns the topics of the posts, the types of actions performed by the members and the interactions among them. Our research shows that such groups create intergenerational “affinity spaces,” which debunks common misconceptions about how seniors approach the digital world.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".