Alternative Perspectives on the Role of Text and Agency in Constituting Organizations
Bibliographic record
Abstract
Organizational discourse analysis, as an area of research, has grown in the past decade. Most scholars posit that language, regardless of the discursive form, is critical to the very nature of an organization. This article contends that discourse is more than an artifact or a reflection of an organization; rather it forms the foundation for organizing and for developing the notion oforganization as an entity. The articles in this volume present different perspectives on the role of text and agency in contributing to the constitution of organizations. Although the concept of text has different meanings in these articles, it refers, in general, to the medium of communication, collection of interactions, and assemblages of oral and written forms. Whether influenced by interaction analysis, structuration theory, text/conversation analysis or textual agency, these essays demonstrate how textuality in all its various forms participates in the production and reproduction of organizational life.
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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 | 0.012 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.006 | 0.062 |
| Scholarly communication | 0.023 | 0.031 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".