Evaluating inductive vs deductive research in management studies
Bibliographic record
Abstract
Purpose The purpose of this paper is to address the imbalance between inductive and deductive research in management and organizational studies and to suggest changes in the journal review and publishing process that would help correct the imbalance by encouraging more inductive research. Design/methodology/approach The authors briefly review the ongoing debate about the “developmental” vs “as-is/light-touch” journal review modes, trace the roots of the prevailing developmental review to the hypothetico-deductive research approach, and contrast publishing deductive and inductive research from the perspectives of authors, editors, and reviewers. Findings Application of the same developmental evaluation and review mode to both deductive and inductive research, despite their fundamental differences, discourages inductive research. The authors argue that a light-touch review is more appropriate for inductive research, given its different logic. Practical implications Specific criteria for the light-touch evaluation and review of and some concrete suggestions for facilitating inductive research. Social implications Advancing knowledge requires a better balance of inductive and deductive research, which can be facilitated by light-touch evaluation and review of inductive research. Originality/value Building on the debate on journal publishing, the authors differentiate the evaluation and review of inductive and deductive research based on their philosophical underpinnings and draw implications of pursuing inductive research for authors, editors, and reviewers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".