Sustaining Learning about Qualitative Inquiry: A Book Review on The Craft of Qualitative Research - A Handbook
Bibliographic record
Abstract
There are only a handful of articles, books, tools, and resources that are truly accessible to the novice qualitative investigator. The literature contains reams of resources that aid researchers to launch the qualitative learning process. However, there are few opportunities to develop the depth, prowess, and creativity needed to sustain lifelong learning. The Craft of Qualitative Research: A Handbook by Kleinknecht, van den Scott, and Sanders is one resource that assists researchers to achieve this objective. Conceptualized as a “handbook,” this book is meant to be used throughout research projects and professional careers. The practice of qualitative inquiry serves as the focal point for all discussions, and this book creates space and opportunities for learners to acquire experiential knowledge through the vicarious experiences of authors. The vividness with which the cases are presented renders a strong motivation in readers to improve how they conduct qualitative inquiry. Although two minor suggestions would have made this book more useful in the field, this book offers important insight into uncommon or unheard methodological topics that investigators may face.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".