Whose Interview Is It, Anyway? Methodological and Ethical Challenges of Insider–Outsider Research, Multiple Languages, and Dual-Researcher Cooperation
Bibliographic record
Abstract
This article focuses on the methodological challenges in one interview of the 60 in-depth interviews that comprise a research study of Israeli Druze currently underway. The study is being conducted by a pair of researchers, one a Canadian living in Israel, an English and Hebrew speaker, and one an Israeli Druze woman, a Hebrew and Arabic speaker. The interview examined here involves two interviewers, two interviewees, three languages and at least two cultural frameworks. The analysis treats the interview as an intrinsic case in order to expose the various contexts of the interview and how they affect the construction of meaning in this complex research situation.
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 | 0.536 | 0.462 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.018 | 0.067 |
| Scholarly communication | 0.026 | 0.024 |
| Open science | 0.005 | 0.014 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".