Research Design: Qualitative, Quantitative, and Mixed Methods Approaches
Bibliographic record
Abstract
Given the increased use of qualitative and mixed methods, and the continued use of quantitative methods, Creswell's third edition of Research Design: Qualitative, Quantitative, and Mixed Methods Approaches is most timely.He not only compares and contrasts these approaches but also promotes a framework, a process, and strategies for the design and conduct of research in the human and social sciences.The book has two parts.The four chapters that make up Part 1, "Preliminary Considerations," describe the basic elements of a research undertaking, such as philosophical assumptions, the literature review, the use of theory, and the writing style and ethics.The six chapters in Part 2, "Designing Research," elaborate on the design components of research, such as the introduction, the research purpose, research questions and problems, and methods and procedures for data collection and analysis.
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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 | 0.210 | 0.231 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.011 | 0.020 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.013 | 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".