Engaging “Care” Behaviors in Support of Employee and Organizational Wellbeing through Complexity Leadership Theory
Bibliographic record
Abstract
During the COVID-19 pandemic, the attributes of nurturing, empathy, and relating rather than directing moved into the spotlight as important skills for leadership. These skills are representative of the concept of “care” that is often associated with women’s or feminine leadership. The importance of care as a component of leadership had not received significant attention in the leadership literature until the pandemic brought the need for care onto center stage. This article argues that care will continue to be an important attribute of leadership and an essential attribute of an androgynous leadership style—that includes behaviors typically classified as male and those behaviors typically classed as female—that is needed to navigate the increasing complexity of the world most effectively. The article further argues that complexity leadership theory provides the most appropriate leadership approach through which complex adaptive organizations can initiate and foster the development of “care” behaviors as part of an androgynous approach to leadership which produces system-wide benefits in complex systems more capable of addressing the global challenges of the climate crisis and increased environmental disasters, future pandemics, local wars, terrorist attacks, and other phenomena.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".