Exploring the connection between organizations and organisms in dealing with change
Bibliographic record
Abstract
Purpose This paper aims to review organizational studies literature and related fields to explore the parallel between organizations and organisms in dealing with change. Design/methodology/approach The authors reviewed the literature to explore organizational change theories. Additionally, they referred to biological studies to explore the connection between organizations and organisms. Findings To cope successfully with change, organizations need to be aware of the critical, vulnerable points that may endanger their survival. These vulnerabilities can arise from external or internal factors or both. Organizational leaders, being aware of these criticalities, can act swiftly to deal with threats while keeping an eye on available opportunities. Research limitations/implications Future research could be conducted on understanding the elements of biological transformations through an in-depth study focused on species that have undergone frequent mutations and adaptations. It is hoped that HRD researchers, especially organization development (OD) theorists and practitioners, can build upon the ideas presented in this article. Practical implications The review and analysis can open doors for HRD practitioners to seek a better understanding of biological transformations, while enabling them to borrow ideas to be used in leading organizational change and design successful organizational change. Originality/value In this paper, the authors selected organizational theories to outline parallels between organizations and organisms to emphasize what organizations can learn from the success of organisms changing over billions of years. Thus, this paper uniquely contributes to HRD literature by encouraging OD researchers to conduct more interdisciplinary research. Most importantly, this paper contributes to understanding the underlying theories in HRD/OD.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.005 |
| 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".