I get by with a little help from my friends: The ecological model and support for women scholars experiencing online harassment
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
This article contributes to understanding the phenomenon of online abuse and harassment toward women scholars. We draw on data collected from 14 interviews with women scholars from the United States, Canada, and the United Kingdom, and report on the types of supports they sought during and after their experience with online abuse and harassment. We found that women scholars rely on three levels of support: the first level includes personal and social support (such as encouragement from friends and family and outsourcing comment reading to others); the second includes organizational (such as university or institutional policy), technological (such as reporting tools on Twitter or Facebook), and sectoral (such as law enforcement) support; and, the third includes larger cultural and social attitudes and discourses (such as attitudes around gendered harassment and perceptions of the online/offline divide). While participants relied on social and personal support most frequently, they commonly reported relying on multiple supports across all three levels. We use an ecological model as our framework to demonstrate how different types of support are interconnected, and recommend that support for targets of online abuse must integrate aspects of all three levels.
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 | 0.001 | 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 | 0.001 | 0.000 |
| 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