A Conversation About the ISIS Crisis and What It Means Locally
Bibliographic record
Abstract
Montgomery County Executive’s Faith Community Working Group and The World Organization for Resource Development and Education (WORDE) hosted a dialogue with the community to talk about the ISIS crisis, and what it means to Montgomery County. imageThe conversation took place on Oct. 8 at the International Cultural Center in Montgomery Village and featured Montgomery County Police Chief Thomas Manger, Rabia Chaudry, founder of Safe Nation Collaborative, Mehreen Farooq, from World Organization for Resource Development and Education, and Hussein Hamdani Esq and Angus Smith, members of the Canadian Cross Cultural Roundtable. During the event faith leaders and law enforcement officials talked about factors that influence an individual to join groups like ISIS or al-Qaida. “As our entire nation worries about terrorist attacks, we need efforts like this to really have the courageous conversation that will hopefully stop something from occurring in our community,” Manger said. The group discussed the ISIS recruiting tactics, and strategies to empower the community to intervene in case they can recognize risk factors on a person leaning toward extremist activities. Sahar Ahamis, associate professor of communication at the University of Maryland, said this type of event is important to raise awareness, and create a policy of prevention and pro-activeness. “We can not have a bipolar position on this. We have to have a united stand in this type of terrorist threats. It has to be an ‘us’ mentality,” Ahamis said. According to the event’s invitation, in the past year more than 100 Americans have attempted to join ISIS or other terror groups in Syria or Iraq.
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 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 | 0.000 | 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 | 0.000 | 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) | 0.151 | 0.003 |
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; both teacher heads agree on what is shown here.
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".