How can institutions better support researchers? The case of extremism and terrorism research
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
Research in certain fields of study may carry emotional and safety-related risks. For example, scholars in the field of extremism and terrorism often navigate potentially uncomfortable or unsafe environments, face an emotional toll when exposed to extreme ideologies or risk facing backlash from extremists, either during the research process or after the publication of their findings or media appearances. However, support provided for them tends to be limited, often due to the lack of institutional awareness of the risks inherent in researching potentially dangerous populations. Drawing on 13 interviews with directors and coordinators of research institutions that have developed guidelines and protocols to protect researchers, as well as 7 internal documents produced by these institutions, this article examines institutional practices for preventing, mitigating and responding to harm, threats and harassment of researchers. The findings emphasize the role of institutions in establishing a safe organizational culture, implementing safety tools and protocols and considering the intersectional nature of risks and challenges.
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 | 0.031 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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