Bibliographic record
Abstract
This research project undertakes a critical analysis of the use of new media technologies by community activists engaging in local and global communities. Increasingly, community organizations are using digital media to augment their various activities and conduct campaigns. I will consider this development with regard to WorldPulse.com, a global organization whose aim is to foster and facilitate civic engagement. More specifically, the website attempts to function and serve as a global public sphere and vehicle for the expression and discussion of political, social and cultural issues relevant to women. The analysis conducted in this thesis focuses on the website’s digital action campaigns on gender-based violence, girl child education, and women’s access to technology between 2012 and 2014, and its ‘Voices of Our Future’ citizen journalism training program. This project employs digital ethnographic methods using content and discourse analysis, participant observation, online web survey, semi-structured email interviews and a researcher’s journal to examine the potential of worldpulse.com to serve as a global public sphere for women. The research makes use of critical studies theories and data triangulation methodologies in order to identify and evaluate if, and to what extent, the site facilitates public sphere activity and activism. I have developed an inductive typology to assess levels and kinds of civic engagement that is enabled and augmented by the interconnection of online and offline advocacy. This thesis aims to contribute to the body of scholarly literature researching and evaluating the extent to which new media technologies enable and facilitate public sphere engagement.
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.
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.016 | 0.015 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".