Performing Theories, Transforming Organizations: A Reply to Marti and Gond
Bibliographic record
Abstract
Marti and Gond (2018) have recently attempted to extend our understanding of how theories shape social reality by developing a process model of performativity and by articulating the boundary conditions that delimit that process. While we laud Marti and Gond's attempt to develop an analytical template to study the effectiveness and influence of theories, and fully share their overarching sentiment about the substantial potential for this kind of theorizing effort, we believe there are two fundamental flaws in their framework. First, Marti and Gond conceptualize a theory as an objectified, standalone entity. Second, they characterize the effects of a theory in terms of a linear, sequential process. In contrast to this view, we conceptualize a theory as inherently relational (i.e., they must be considered in conjunction with actors, artifacts, practices, and other theories) and characterize the effects of a theory in terms of dynamic, non-linear processes. We believe that conceptualizing theories relationally and characterizing the effects of theories dynamically enhances the generative potential of performativity for management research.
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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 | 0.023 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.008 | 0.018 |
| Scholarly communication | 0.010 | 0.021 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.050 | 0.076 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".