Community Responses to Violence in Holman, Northwest Territory
Bibliographic record
Abstract
Introduction. When we talk about narrative, we often focus on the story and the teller, but rarely on the listener. Yet often the first step in healing is finding someone who will listen to you and truly hear your story. Alice Kimiksana and others in the Canadian Arctic village of Holman, who are concerned about the community’s high suicide rate, understand this basic healing principal very well. They have worked together to create a Help Line—a confidential listening and crisis intervention program—for their community. Kimiksana talks about how in Holman, as in other northern communities, trauma led parents to teach their children not to talk about their pain, their fear, or their abusive experiences, including those that occurred in the residential schools. As a result, even years later, the pain, fear, and hurt can become unbearable, leading sometimes to alcohol and drug abuse, and sometimes to violence toward oneself or others. Educational groups, Healing Circles, and youth groups are starting to help. However, unless there are helpers who will listen when people begin to tell their stories, this first step in healing cannot take place and the cycle of intergenerational trauma will not be broken. Kimiksana planned on giving her presentation jointly with Holman Elder, Kate Inuktalik, but her co-presenter became ill on route to Quebec City. After recuperating in the Yellowknife Hospital, Kate Inuktalik returned home. Kimiksana made sure her friend would be well taken care of, then proceeded to Quebec City and gave the presentation. WHA
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".