“You shouldn’t have to get that approved”: Journalists as research participants and feminist research methods interventions
Bibliographic record
Abstract
In this short piece, I discuss the ethnographic methods employed for the data collection portion of my dissertation on sexual violence news coverage in Canada, as well as the ethical and methodological questions I considered when designing this research plan.I bring them into conversation with feminist research on collaborative approaches and digital research ethics as well as journalism studies to discuss how my project intervenes in these fields.I argue that a collaborative research approach highlights the enduring role of objectivity and distance in journalism, not only with regard to how journalists evaluate and navigate their own authority, but also the authority of researchers with whom they come into contact.Further, the approach allows for insight in sexual violence news coverage and the methods of journalists themselves: as I argue, the negotiations, adversarial nature of some interactions, and conversations around sharing transcripts and other methods of collaborative research are valuable both to academics researching (with) journalists and journalists writing on/with/against sexual violence survivors.In designing the research methods for this section of the research, I was in conversation with a number of scholars who explore anti-oppressive methods of scholarship.While this research is not participatory action research-participants were not consulted about the research
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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 | 0.072 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.004 |
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; both teacher heads agree on what is shown here.
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".