Navigating Power Dynamics in Virtual Interviews with Sex Workers during COVID-19: A Researcher-Participant Perspective
Bibliographic record
Abstract
Sex workers may show extreme sensitivity to power relations during qualitative research due to the previous experiences of stigmatization and marginalization. The purpose of this article is to analyze how technologically mediated communication between researchers and participants during an interview may influence the scope of control exercised by the interactional partners. During the first wave of the COVID-19 pandemic, I conducted 16 qualitative phone and videoconference interviews with female sex workers in Poland discussing the social stigmas they encounter. Each interview was followed up with extensive field notes that were analyzed using the procedures of grounded theory methodology. These very field notes serve as the basis for the paper herein. As a result of the analysis, I distinguished areas of power negotiated by the interviewer and interviewees in successive phases: before, during, and after the interview. The sense of control over the respective aspects of a study may contribute to the establishment of a more democratic power relationship between the researcher and the participants who belong to a population bearing a stigma.
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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 | 0.012 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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".