Bibliographic record
Abstract
Purpose The purpose of this paper is to assist an organization to restructure as a bi‐modal organization in order to achieve sustainability in today's highly complex business world. Design/methodology/approach The paper is conceptual and is based on relevant literature and the authors' research and practice. Findings Although fluid self‐organizing networks are the natural state for humankind, in most organizations “organizing” entails the process of autopoiesis. This process does not produce the open fluid organization that is required for success in today's business world. While autopoiesis is taking place, informal socialization is taking place across the organization's interpersonal networks. Under supportive conditions, this leads to the development of a bi‐modal organization where one or more open systems may emerge and co‐exist concurrently with the autopoietic system; these open systems include fluid networks and complex adaptive system. The bi‐modal organization achieves sustainability by balancing a certain amount of organization versus a certain amount of instability, leading to predictability with disorder, and planned long‐term strategy achieved through many concurrent short‐term actions. Research limitations/implications Future research will involve an empirical study that will further examine the bi‐modal organization, its development, and its properties. Practical implications The systems that surround a business organization now and for the foreseeable future are highly dynamic, competitive, and socially individualized, and demand a new organizational form and competencies that may only be exhibited by a bi‐modal organization based on an open system. The paper describes how an organization can restructure to become a bi‐modal organization. Social implications The paper should help improve quality of work‐life and organizational structure. Originality/value The paper describes a new organizational form designed to flourish in today's complex business contexts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".