Walking the Tightrope: Ethical Issues for Qualitative Researchers
Bibliographic record
Abstract
Walking the Tightrope is the sort of timely and valuable work that belongs in the hands of every Canadian graduate student contemplating a participant observation and/or interview based thesis or dissertation. All of the most central issues confronting qualitative researchers who are accountable to research ethics boards (REBs) and Tri-Council requirements are addressed in the text. The volume is strengthened by: the mix of perspectives it brings to the issues raised (e.g. senior scholars with multiple ethnographies to their credit and newer voices within the academy), the multiple theoretical positions reflected in the text (e.g. symbolic interaction, participatory action research, standpoint theory) and the range of field studies engaged (e.g. cyberspace, social work, persons with developmental disabilities, and school settings). One always engages a text from a particular position with a mixture of insight and blindness. In my case, I come to this text from multiple vantage points as an ethnographer who tends to focus on matters of deviance and deviance regulation, as a teacher of an ethnographic research sequence where students actually get their hands dirty, as a former faculty association president and, currently, as a university administrator. My choice of issues to address in this review is influenced by these multiple commitments. I highlight three themes within this volume.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.425 | 0.473 |
| Meta-epidemiology (narrow) | 0.001 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.030 | 0.098 |
| Scholarly communication | 0.042 | 0.025 |
| Open science | 0.008 | 0.024 |
| Research integrity | 0.019 | 0.029 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier 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".