Learning the Concept of Researcher as Instrument in Qualitative Research
Bibliographic record
Abstract
The authors describe the process whereby a student with a background in economics was guided to understand the central role in qualitative research of the researcher as instrument. The instructor designed a three-part mock research project designed to provide experiential knowledge of the enterprise of qualitative research. Students, as neophyte qualitative researchers, were guided to develop a sophisticated understanding of the necessity for congruence between the ontological and epistemological philosophical underpinnings of the research question, data collection techniques, and analysis. An example of the trail of analytic decisions one student made during analysis is included to show the complexity of qualitative analysis and interpretation.
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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 | 0.302 | 0.357 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.009 | 0.069 |
| Scholarly communication | 0.018 | 0.032 |
| Open science | 0.005 | 0.021 |
| Research integrity | 0.010 | 0.023 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".