Bibliographic record
Abstract
In recent years, there have been many calls for scholars to innovate in their styles of conceptual work, and in particular to develop process theoretical contributions that consider the dynamic unfolding of phenomena over time. Yet, while there are templates for constructing conceptual contributions structured in the form variance theories, approaches to developing process models, especially in the absence of formal empirical data, have received less attention. To fill this gap, we build on a review of conceptual articles that develop process theoretical contributions published in two major journals ( Academy of Management Review and Organization Studies) to propose a typology of four process theorizing styles that we label linear, parallel, recursive and conjunctive. As we move from linear to parallel to recursive to conjunctive styles, conceptual reasoning becomes more deeply embedded in process ontology, while the standard structuring devices such as diagrams, tables and propositions traditionally employed in conceptual articles appear less useful. We offer recommendations that may be helpful in enriching and deepening process theoretical contributions of all types.
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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 | 0.025 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.005 | 0.033 |
| Scholarly communication | 0.022 | 0.041 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".