Standby Ties that Mobilize: Social Media Platforms and Civic Engagement
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
Nonprofit organizations and groups depend on donations and volunteers for their survival. Digital media can help by offering a platform for making online donations and facilitating online volunteering, but also by identifying and connecting with people who are sympathetic to an organization’s mission. This article employs four-country (USA, UK, France, and Canada) representative survey data ( n = 6291) to examine the use of social media for establishing connections between citizens and organizations as well as the relationship of these connections to online and offline volunteering and donating. Across all social media platforms considered (Facebook, Instagram, and Twitter), I find significant positive correlations of following nonprofits with online and offline volunteering and donating. However, Facebook has a slightly larger role, which may be attributed to its overall popularity, which can incentivize organizations’ more intense use of this platform.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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