Using Constructivist Case Study Methodology to Understand Community Development Processes: Proposed Methodological Questions to Guide the Research Process
Bibliographic record
Abstract
Often, research projects are presented as final products with the methodologies cleanly outlined and little attention paid to the decision-making processes that led to the chosen approach. Limited attention paid to these decision-making processes perpetuates a sense of mystery about qualitative approaches, particularly for new researchers who will likely encounter dilemmas and uncertainties in their research. This paper presents a series of questions that assisted one Ph.D. student in making key methodological choices during her research journey. In this study, a collective case study design informed by constructivist grounded theory data analysis methods was used to develop a framework of community development from an occupational therapy perspective. Ten methodological questions are proposed regarding research question development, research paradigm, design and analysis, and trustworthiness. Drawing on examples from this research project, these questions are used to explicate the decisions made “behind the scenes”, with the intention of providing both theoretical and practical guidance to others embarking on similar research journeys.
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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 | 0.256 | 0.152 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.010 | 0.027 |
| Scholarly communication | 0.017 | 0.020 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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, 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".