Stewards, Mediators, and Catalysts: Toward a Model of Collaborative Leadership1
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACTLeadership is widely recognized as an important ingredient in successful collaboration. Collaborative leaders typically play a facilitative role, encouraging and enabling stakeholders to work together effectively. Building on the existing literature on collaborative governance and interviews with leaders of U.S. Workforce Investment Boards, we identify three facilitative roles for collaborative leaders. Stewards facilitate collaboration by helping to convene collaboration and maintain its integrity. Mediators facilitate collaboration by managing conflict and arbitrating exchange between stakeholders. Catalysts facilitate collaboration by helping to identify and realize value-creating opportunities. Although collaborative leaders are called upon to play multiple roles, the salience of these roles may vary with the circumstances and goals of collaboration. In situations of high conflict and low trust, for example, collaborative leaders may be called upon to emphasize steward and mediator roles. In situations where creative problem-solving is the primary goal, the catalyst role may become much more central. Distinguishing these three collaborative leadership roles is an important step toward building a contingency model of collaborative leadership.Keywords: collaboration, collaborative governance, stakeholder, contingency, leadership, workforce development.IntroductionIn 1998, President Clinton signed into law the Workforce Investment Act (WIA). Much like the welfare reform, enacted only two years earlier, WIA promised to revolutionize the work of workforce development. Although the federal government had long been a supplier of workforce training programs under programs enacted through the Job Training Partnership Act (JTPA) or the Comprehensive Employment and Training Act (CETA), these programs offered a patchwork approach to job training. According to former Labor Secretary Alexis Herman, these programs were -never fully brought into alignment with other components of the system'. Consequently, federally funded job training programs were largely scattered - offering clients limited access to services, career advice, quality job information data, and skills training.2 It was hoped that through coordination and co-location at the servicedelivery level (e.g., one stop shops), consumers would have easier access to every element of the workforce development system, from simple job searches to receiving advice on career planning, to enrolling in basic more advanced skills training. However, coordination of service delivery was only one of the problems plaguing an increasingly dysfunctional workforce system, so policymakers also mandated a more comprehensive strategy of collaboration. The WIA placed control of each local workforce area (established by governors) in Workforce Investment Boards (WIBs), which would be jointly governed by labor unions, community colleges, training providers, locally elected officials, industry leaders, and social service providers. These stakeholders were to develop collaborative strategies to create a more effective workforce system.Despite this mandated collaborative framework, large variations developed in the degree, scope, type, and breadth of collaboration among workforce development areas. Some workforce development areas practiced pro forma collaborative governance - presenting only enough of a veneer of collaboration to please local and federal officials. Others surpassed this by implementing micro-collaboratives- supplementing the WIB's governance with smaller project-based forms of collaborative governance. A small but growing number of WIBs engaged in more extensive collaborative governance. In each of these cases, leaders played a critical role in shaping the depth and extent of WIB collaboration. Leaders of the most collaborative WIBs, for example, have begun to reassess what one referred to as the little fiefdoms' established by governors under WIA - workforce areas established along political rather than economic lines. …
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it