The enduring field: Exploring researcher emotions in covert research with antagonistic organisations
Bibliographic record
Abstract
This paper explores the emotional dimensions of doing covert research with antagonistic organisations. Drawing on the experiences of three researchers who identify as lesbian, gay, and LGBT ally, who covertly attended public and semi‐public conferences and events organised by groups with heteroactivist positionings over two years, we consider the multiple, nuanced and complex emotional dimensions of being “behind enemy lines” (Jansson, ). We argue for greater consideration of the emotional spaces covert research creates, as in our case a “closet” space was produced which suppressed our sexualities or allyship. Furthermore, we argue that the process of doing covert research is one that both precedes and exceeds being in the field, and as such, we need to pay attention to researcher emotion as a process that begins long before we step into the field and continues long after we leave.
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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 | 0.044 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.017 | 0.051 |
| Scholarly communication | 0.016 | 0.013 |
| Open science | 0.002 | 0.022 |
| Research integrity | 0.004 | 0.007 |
| 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".