Reflections From Applying Intersectionality to a Constructivist Grounded Theory Study on Intimate Partner Violence and Trauma
Bibliographic record
Abstract
In this research note, I reflect on conducting a qualitative study on trauma and intimate partner violence (IPV), applying an intersectional lens to constructivist grounded theory methodology. I argue that despite offering an ability to critically examine socially constructed categories of identity, and providing a way to ensure the active inclusion of social justice goals into research, intersectionality is underused within social work research. I also reflect on the particular importance of an intersectional lens in countering the previously identified assumptions of sameness underlying IPV and trauma services. From recounting my research process, I discuss recommendations for further intersectional research, and research on trauma. Recommendations include allowing enough time for recruitment and analysis, making visible the researcher’s role, including a participatory element in studies, and ensuring continuous critical and reflexive processing at all research stages.
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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 | 0.236 | 0.165 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.037 | 0.155 |
| Scholarly communication | 0.038 | 0.048 |
| Open science | 0.008 | 0.071 |
| Research integrity | 0.009 | 0.032 |
| Insufficient payload (model declined to judge) | 0.004 | 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".