Ethics in Qualitative Research: A View of the Participants' and Researchers' World from a Critical Standpoint
Bibliographic record
Abstract
This paper illustrates how certain ethical challenges in qualitative research necessitate sustained attention of two interconnected worlds: the world of the researcher and the world of the participant. A critical view of some of the ethical challenges in the participants' and researchers' world reveals that how we examine both these worlds' effects how we design our research. In addition, it reflects the need for researchers to develop an ethical research vocabulary at the inception of their research life through multiple modes. The modes may include dialogue in the spoken and written and visual to affect their aims to adhere to the principles of respect, beneficence, nonmaleficence, and justice in a way that is mutually beneficial to the participant and the researcher. Further, the deliberations in this paper reveal that a critical conscious research ethics are embedded in the unfolding research ethics process involving the participants and the researchers, and both the participant and researcher add equal weight to the transparency of the ethical process and add value to building methodological and ethical rigor to the research.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Research integrity Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
| gpt | Metaresearch Domain: Methods · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | medium |
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 | 0.259 | 0.168 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.023 | 0.124 |
| Scholarly communication | 0.029 | 0.030 |
| Open science | 0.005 | 0.019 |
| Research integrity | 0.012 | 0.018 |
| Insufficient payload (model declined to judge) | 0.003 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".