Seven Snags of Research Ethics on the Qualitative Research Voyage
Bibliographic record
Abstract
Responsible researchers with ethically sound research skills are fundamental to success in an ever-changing business and social world. Embedding ethics into research by students seems to be intuitively easy given tight, standardized ethical guidelines and rigorous ethical approval process in the university. In reality, there are Masters and PhD research students who feel ill-prepared when they encounter ethical ambiguities and complexities in the field which are unique, beyond what they had foreseen at the outset of a qualitative inquiry or were prescribed, advised and forewarned by a research ethics committee (REC). The aim of this conceptual paper is to discuss seven pitfalls of research ethics in a qualitative research voyage in order to educate and sensitize current and prospective research students. The seven pitfalls are: (1) complexity and ambiguity of informed consent; (2) embedding informed consent as a process rather than an event; (3) navigating the moral conundrum of unintentional disclosure; (4) dealing with deductive disclosure; (5) dialectic between participant`s desire for recognition and greater confidentiality; (6) researcher role conflict and (7) difficulty of embedding researcher reflexivity. The paper concludes that only research students who are ethically literate and actively reflexive in the entire research process are more likely to know whenever they encounter ethical pitfalls, deal with them properly; and ultimately entrench relevant skills to conduct ethically sound research. Highlighted are implications for research educators to develop research competence of current and future researchers. Responsible researchers with ethically sound research skills are fundamental to success in an ever-changing business and social world. Embedding ethics into research by students seems to be intuitively easy given tight, standardized ethical guidelines and rigorous ethical approval process in the university. In reality, there are Masters and PhD research students who feel ill-prepared when they encounter ethical ambiguities and complexities in the field which are unique, beyond what they had foreseen at the outset of a qualitative inquiry or were prescribed, advised and forewarned by a research ethics committee (REC). The aim of this conceptual paper is to discuss seven pitfalls of research ethics in a qualitative research voyage in order to educate and sensitize current and prospective research students. The seven pitfalls are: (1) complexity and ambiguity of informed consent; (2) embedding informed consent as a process rather than an event; (3) navigating the moral conundrum of unintentional disclosure; (4) dealing with deductive disclosure; (5) dialectic between participant`s desire for recognition and greater confidentiality; (6) researcher role conflict and (7) difficulty of embedding researcher reflexivity. The paper concludes that only research students who are ethically literate and actively reflexive in the entire research process are more likely to know whenever they encounter ethical pitfalls, deal with them properly; and ultimately entrench relevant skills to conduct ethically sound research. Highlighted are implications for research educators to develop research competence of current and future researchers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.358 | 0.191 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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; both teacher heads 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".