When Communication Shapes the Self-Managed Organization
Bibliographic record
Abstract
The Self-Managed Organization (SMO) – an organizational form promoting distributed responsibility and higher levels of autonomy among employees – has been a growing topic of conversation in modern organizations. Indeed, firms increasingly acknowledge the potential of collective power over a firm’s strategy making process – enhanced when all employees autonomously organize and act towards a firm’s corporate vision and stakes. Nevertheless, enacting SMO is challenging for organizations. First, SMO requires sustained upper management communication to entice employees to autonomously move from a hierarchy- centric a stake-centric organization. Second, SMO requires organized communication among employees to collectively distribute strategic responsibility. Therefore, to better theorize the Self-Managed Organization, we adopt a Communication as Constitutive of Organizations’ (CCO) perspective since SMO can only be enacted in and through communication. We also strengthen CCO’s claims with evidence from an emerging area of investigation – new organizational forms. Our results – based on an empirical study conducted at one of the few existing self-managed multinationals – demonstrate how communication has the power of enacting and stabilizing a new organizational form. Indeed, we expose how SMO is enacted and stabilized when performativity of strategy occurs in a communication praxis.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.020 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".