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 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 | 0.011 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".