Structuration bridging diffusion of innovations and gender relations theories: a case of paradigmatic pluralism in IS research
Bibliographic record
Abstract
Abstract This paper discusses the adoption of a pluralist theoretical framework – one that is also multiparadigmatic – for conducting and publishing information system (IS) research. The discussion is illustrated by a single case study involving the Australian cotton industry. The theoretical framework is informed by three sociological theories, each with its particular paradigmatic assumptions: structuration theory as a meta‐theory, and diffusion of innovations and gender relations as lower‐level theories from notionally opposing paradigms. Theoretical pluralism helped to produce rich findings, illuminating both the social nature of women farmers' roles, the materiality of the cotton farming context, the characteristics of the decision support systems in use and the recursive way in which human agency and institutional pressures shape each other. Because users of so‐called divergent paradigms often face criticism based on the incommensurability issue, one of the main contributions of this paper is to discuss the value of a pluralist and multiparadigmatic theoretical framework in dealing with complex IS social phenomena.
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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 | 0.060 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.013 | 0.064 |
| Scholarly communication | 0.015 | 0.020 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".