The Sage Handbook of Qualitative Research in Organizational Communication. Boris H. J. M. Brummans, Bryan C. Taylor, and Anu Sivunen (Eds.)
Bibliographic record
Abstract
Organizational communication is not only a discipline, but also a community. It has its meeting places, such as the annual conventions of the National and International Communication Associations. It has its rituals, such as business meetings and award ceremonies during these conferences. Unfortunately, however, the field has few outlets to showcase its research. Management Communication Quarterly is the field’s only flagship journal. Moreover, for a long time, The Sage Handbook of Organizational Communication (Putnam & Mumby, 2013), which has gone through several editions, was the only comprehensive volume presenting the discipline’s “state of the art.” Recently, this has started to change. In 2017, Craig Scott and Laurie Lewis edited the impressive International Encyclopedia of Organization Communication (Scott & Lewis, 2017). In 2021, François Cooren and Peter Stücheli-Herlach edited the Handbook of Management Communication (de Gruyter) (Cooren & Stücheli-Herlach, 2021). And in 2022, Joëlle Basque, Nicolas Bencherki, and Timothy Kuhn edited The Routledge Handbook of the Communicative Constitution of Organization (Basque et al., 2022). In addition, Vernon Miller and Marshall Scott Poole are about to publish a new Handbook of Organizational Communication (in press).
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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 | 0.019 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.026 | 0.017 |
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".