Social Identities, Group Formation, and the Analysis of Online Communities
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
Central to research in social psychology is the means in which communities form, attract new members, and develop over time. Research has found that the relative anonymity of Internet communication encourages self-expression and facilitates the formation of relationships based on shared values and beliefs. Self-expression in online social networks enables identity experimentation and development. As identities are fluid, situationally contingent, and are the perpetual subject and object of negotiation within the individual, the presented and perceived identity of the individual may not match reality. In this chapter, the authors consider the psychological challenges unique to understanding the dynamics of social identity formation and strategic interaction in online social networks. The psychological development of social identities in online social network interaction is discussed, highlighting how collective identity and self-categorization associates social identity to online group formation. The overall aim of this chapter is to explore how social identity affects the formation and development of online communities, how to analyze the development of these communities, and the implications such social networks have within education.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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