Methodological Opportunism in Management: The Use of the Case Study Method to Develop a New Construct Called IODD
Bibliographic record
Abstract
The different visions that organizational reality conveys generates a diversity of research methods allowing it to be approached from different perspectives. Such diversity of paths to reality in organizations often poses epistemological problems. In fact, by migrating from one vision of the organization to another we go through a continuum from subjective to objective and the methods of investigation change accordingly. In management sciences, this epistemological opposition between the positivist perspective and the constructivist one results in two research directions. Research traditions in management sciences generally mean that confirmatory research relies on quantitative techniques and exploratory research tends to adopt qualitative methods. However, can we really speak about antagonism between positivism and constructivism in management science? If not, what are the epistemological foundations of the case study as a research strategy in management sciences? Such a response marks, in our opinion, the need to adjust research paradigms by putting an end to the opposition between positivist positioning and constructivist positioning. Especially since such an opposition has been falsified since Piaget (1970) then by Latour (1991).
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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 | 0.135 | 0.116 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.021 | 0.012 |
| Science and technology studies | 0.008 | 0.052 |
| Scholarly communication | 0.021 | 0.023 |
| Open science | 0.004 | 0.023 |
| Research integrity | 0.005 | 0.008 |
| 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, 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".