Collective Trauma as a Personal/Social Concern for Persons within Marginalized Communities
Bibliographic record
Abstract
Much of the literature about trauma has conceptualized trauma only as a personal and psychological issue (Herman, 1992). This paper is a departure from this as it attempts to shed light on trauma as a community process such as the complex community responses to the experience of pervasive and ongoing injurious acts. The authors, with assistance from a Social Sciences and Humanities Research Council standard research grant, interviewed participants who are involved in community practice in three marginalized communities within two Canadian urban centers: 1) gay, lesbian, bisexual, transgendered, transsexual, and queer people; 2) Aboriginal people; and 3) Salvadorian refugees to understand social disruption that results from marginalization based on identity. In this paper, we argue that such a disruption, trauma, is shared across communities even if experienced differentially. We found that the participants’ experiences of trauma were expressed as both a personal and as a shared experience. Because of shared community identity, one did not have to experience the traumatic event personally to share in it. The participants of the research understood trauma to be deleterious and harmful but also allowed for an openness and affinity to others within their communities. Thus, trauma, while having serious negative impacts from its origins in social prejudice and mistreatment from outside the community, can also be seen as a basis for organization and resistance within marginalized diverse communities.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.041 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".