Bibliographic record
Abstract
This thesis investigates the dynamics of women-designed and women-focused online communities, specifically through the case study of WomenOverseas (Tā Xiāng), a platform supporting Chinese women and non-binary individuals in diaspora within a censored digital environment.The study's main objective is to discern the varying empowerment dimensions within WomenOverseas, offering insights into its alignment with the needs and experiences of women from non-Western perspectives.The methodology includes a literature review exploring empowerment from a feminist perspective and evaluating the role of women-centric online communities.It employs thematic and content analysis with semi-structured interviews among the community's users and moderators, using inductive and deductive coding to pinpoint themes of online empowerment for women.This analysis reveals significant contrasts between the experiences of these individuals on mainstream Chinese platforms and within WomenOverseas, underscoring a journey from disempowerment to empowerment and belonging.Key themes identified include "Selective Inclusivity," "Towards Collective Wisdom," and "The Positive Feedback Loop of Revelation, Validation, and Contribution," each reflecting the facilitators, obstacles, and nuances in this transformative process.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".