Bibliographic record
Abstract
Social media blurs the boundaries of social life and brings together different spheres such as family, work or friends in the same online space. Users begin to post less intimate details about themselves, and they want to see fewer details of the private lives of others as well. Users want to better control what they read on social media. This paper studies the use of information and communication technology in social and cultural context. A qualitative approach provides a rich and detailed description of contexts and motivations of social media use. It shows that users are still negotiating the endless flow of information coming from social media. Keywords: context collapse, boundary, privacy, social media, media connectivity, boundary regulation practices, oversharin *** Résumé : Les médias sociaux efface les frontières de la vie sociale et regroupe différentes sphéres tel que la famille, le travail ou les amis dans un même espace en ligne. Cependant, les usagers commencent à moins diffuser des détails intimes sur eux-mêmes, et ils veulent moins voir les details de la vie privée des autres. Les usagers cherchent à mieux controler ce qu’ils lisent sur les médias sociaux. Cet article étudie l'utilisation des technologies de l'information et de la communication dans le contexte social et culturel. Une approche qualitative fournit une description riche et détaillée des contextes et des motivations de l'utilisation des médias sociaux. L’article montre comment et pourquoi les utilisateurs négocient le flux incessant d'informations provenant de médias sociaux. Mots-clés : éffondrement de contexte, médias sociaux, protection de la vie privée, partage d’information
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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 | 0.023 | 0.125 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.013 | 0.022 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".