This chapter begins to ask about the appropriateness of the governance structures given context. Chapter 18 described the structures of governance. This chapter seeks to understand what those structures might mean.
Governance does not happen in isolation from the policy area and institutional activity. Rather, it is the bridge between them. “The purpose of governance is to assure that higher education’s stakeholders are able to achieve the goals they have for the enterprise” (OECD, Reference Maassen, Amaral, Bleiklie and Musselin2017b, p. 260). How well a particular approach to governance is designed to serve as this bridge is important to this discussion, and the focus of this chapter and the next. The previous comparison chapter highlights four different patterns of University governance structure across the fifteen countries of focus – academic-focused, state-extended, internal/external, and the external civic.
Governance is about execution, the ability of agents to carry out the wishes of principals (Austin & Jones, Reference Austin and Jones2016; Fukuyama, Reference Fukuyama2013). Therefore, the question explored here is how appropriately structured is the approach to governance suited for the principals’ aims given the realities of the context in which the universities operate? The fact that the performance of governing bodies is extremely difficult to discern (Chait, Holland & Taylor, 1993; Daily, Dalton & Cannella, Reference Daily, Dalton and Cannella2003; Forbes & Milliken, Reference Forbes and Milliken1999) makes understanding the degree of fit between the governance context and the structure a plausible logic to explore.
Structure is not the only factor in governance capacity. Execution matters – how well the governance actors operate within the presented structures. Common wisdom as well as academic research acknowledge that the use of organizational and decision-making structures may have little relationship to their intended objectives and expectations of their designers (Brunsson & Olsen, Reference Brunsson and Olsen1997; Jibladze, Reference Jibladze2017). “Reform and response will thus not be the outcome of a near perfect rational choice but will be limited in its capacity to deal with complex realities” (Enders, de Boer & Weyer, 2012, p. 9). Structures do the best they can but are unlikely perfect. However, they do matter, as they provide the framework for action, and they must operate in the given context.
This chapter focuses on the nexus of two elements, bureaucratic or public sector capacity and autonomy, drawing on the framework of Fukuyama (Reference Fukuyama2013). Chapter 20 retains the dual-element focus and changes the second dimension to the amount of competition in the system, using the logic of Aghion, Dewatripont, Hoxby Mas-Colell, Sapir, and Jacobs (Reference Aghion, Dewatripoint, Hoxby, Mas-Colell, Spair and Jacobs2010). Both chapters use dimensions of autonomy as a common anchor.
19.1 Autonomy as Common Anchor
Autonomy is the organization’s ability and capacity to act in relationship to its environment, independent from external control (Enders, de Boer & Weyner, Reference Enders, De Boer and Weyer2013). It is an important condition that allows universities to fulfill their missions (EUA, 2017) and ensures that organizations have the authority and capacity to direct their own efforts rather than have them dictated for them. It is a key indicator of organizational development (Brunnson & Sahlin-Andersson, 2010). Finally, autonomy isn’t an absolute but rather is “contextually and political defined” (Neave, 1988, p. 31) and it evolves in response to changing conditions and policy connections. Thus, it varies across country and within policy contexts.
To determine the levels and forms of autonomy across the fifteen countries in this project, the analysis draws on the University Autonomy in Europe framework advanced by the European Universities Association (EUA). This comprehensive framework investigates autonomy across four different dimensions, collectively drawing on over thirty indicators (EUA, 2017):
organizational – a University’s capacity to determine its internal organization and decision-making processes;
financial – a University’s ability to manage its funds and allocate its budget independently;
staffing – a University’s ability to recruit and manage its human resources as it sees fit; and
academic – a University’s capacity to manage its internal academic affairs independently.
Where data is available about the post-Soviet countries (Estonia, Latvia, and Lithuania), this effort draws directly upon the EUA’s scorecard. Outside of the European scorecard effort, EUA independently conducted autonomy audits of Armenia, Moldova, and Ukraine as part of the ATHENA project 2012–2015 (EUA, 2015). The effort produced percentage scores and narrative insight to classify the autonomy level of each country. The remaining nine countries are assigned autonomy levels based on our own rough analysis, as described below. Kazakhstan also had its level of autonomy assessed (EUA, 2018). Since the time of that report, the different levels of autonomy by institutional mission have been consolidated into a common approach. Kazakhstan continues its transition toward governmental goals of increased autonomy, and it remains in transition (Hartley, et al, 2015). Thus, we rely only peripherally on the EUA report. Because a comprehensive analysis of autonomy in former Soviet countries does not exist, this analysis draws on data collected at different points in time, beginning in 2015 (for the ATHENA project countries) through 2021.
Particularly relevant to University governance structures are three dimensions of the EUA framework – organizational, financial, and academic autonomy. The staffing dimension is a management issue and thus not included in this governance analysis. For non-EUA countries, we developed rough (and comparably incomplete) indicators of autonomy based on information in the country profiles, drawing on select indicators from the EUA framework. Specifically for organizational autonomy, we considered the ability of the governing body to hire and fire the president or rector; for financial autonomy, the ability to determine budgets and to generate and keep revenue; and for academic autonomy, the ability to determine academic program offerings and the curricula of those programs. These are focused but also limited conceptualizations of autonomy compared to the comprehensive EUA scorecard framework. Given the lack of numerical scores parallel to EUA’s efforts, each was assigned a mid-range number for comparison. This is not ideal; however, the focus of this effort is not to determine, benchmark, or evaluate autonomy but rather to understand the appropriateness of the governance structure to context. Autonomy is a central element of that context and modest indicators satisfice for this purpose.
Following the lead of EUA (2017), we classify each remaining country’s higher education system level of autonomy across a four-part scale: high, medium-high, medium-low, and low. Table 19.1 provides a snapshot of country-level autonomy.
Table 19.1 Levels of higher education autonomy by country
| Levels of autonomy | Country |
|---|---|
| high levels | Estonia, Kazakhstan (Nazarbayev University) |
| medium-high levels | Latvia, Lithuania, Kazakhstan (State Universities) |
| medium-low levels | Armenia, Azerbaijan, Georgia, Moldova, Ukraine |
| low levels | Belarus, Kyrgyzstan, Russia, Tajikistan, Turkmenistan, Uzbekistan |
19.2 Governance Structure via Capacity and Autonomy
One way to understand the appropriateness of University governing structures is through the nexus of capacity, the ability of the governance system to produce and execute, and autonomy, its level of discretion it has to carry out its functions. Fukuyama (Reference Fukuyama2013) argues that public sector or bureaucratic capacity and autonomy are two contextual dimensions that while independent must be appropriately aligned within a governance context. “More or less autonomy can be a good or bad thing depending how much underlying capacity a bureaucracy has” (Fukuyama, Reference Fukuyama2013, p. 360). Autonomy is important because it leads to creative problem solving and, where it aligns with capacity, has fewer transactional costs than compliance. Autonomy increases when there are fewer rules and broader mandates, with a decentralized or local locus of control rather than a centralized state one.
More or less bureaucracy also can be a good or bad thing depending on the amount and type of autonomy. A low-quality bureaucracy can have too much autonomy allowing decision-makers to pursue poor priorities and in extreme situations can lead to high corruption. Fukuyama (Reference Fukuyama2013) posits Klitgaard’s (1988) formula Corruption = Discretion – Accountability as extreme evidence. See Osipian (Reference Osipian2017) for a discussion of the relationship between autonomy and corruption in Ukrainian higher education as an example from the region.
A high-quality bureaucracy also can have too little autonomy constraining its professionals. “The higher the capacity of a bureaucracy, then, the more autonomy one would want to grant them” (Fukuyama, Reference Fukuyama2013, p. 361). Given the capacity of the governance structure, the problem also can be one of excessive rules or excessive discretion. In a low-quality situation, one would need extensive rules to guide actor behavior. “If an agency were full of incompetent, self-dealing, political appointees, one would want to limit their discretion and subject them to clear rules” (Fukuyama, Reference Fukuyama2013, p. 360). A paper on reform in Ukrainian higher education addresses this point by asking, “What level of self-governance can be delegated to the organizations, which have little public trust, yet receive considerable public funding? How one can provide more autonomy to highly centralised institutions without turning them into feudal domains of the individual rectors?” (Sovsun, Reference Sovsun and Nikolaiev2017, p. 9). Capacity linked to autonomy is needed to address these potential shortcomings. On the other hand, in a high-quality structure, one would not want to limit the professional judgment through overly cumbersome rules to encourage innovative problem solving. “In a high-capacity state, one would like to have more rather than less discretion” (Fukuyama, Reference Fukuyama2013, p. 361).
This framework suggests that a relative ideal exists in balancing appropriate and corresponding levels of autonomy and capacity. It further suggests that changing a level of autonomy is best done in proportion to appropriate system capacity. More autonomy matches higher levels of capacity; less capacity is likely better aligned with low levels of autonomy. In the University governance context, then, systems with high capacity should have high levels of autonomy, and the inverse would also be desirable.
However, there exists a possible paradox in this rationale worthy of attention. One might argue that if the government cannot function well, delegation may be the answer, removing decision-making out of central control to devolved control. The challenge here is that the State likely doesn’t have the capacity to monitor performance across a set of autonomous entities. The policy guardrails and accountability frameworks likely needed to ensure that the delegated powers are functioning with the country’s best interests at a variety of local levels won’t exist.
Autonomy, Capacity, and Governance Structures
This analysis focuses on the perceived levels of capacity or quality of the bureaucracy and the level of autonomy provided to its institutions. It then overlays the current University governance structure over these dimensions to determine the extent to which the approach seems to map appropriately onto country-level government quality and autonomy. Does the structure provide too much autonomy given capacity? Does capacity seem to outstrip the level of autonomy?
To determine country context regarding quality and government capacity, this analysis draws on a set of indicators from the World Bank (WB) (2019) and World Economic Forum (WEF) (Schwab, Reference Schwab2019) to develop an estimate of bureaucratic capacity. These indicators were not developed for this purpose, so the analysis is indirect and likely inexact. Each indicator independently measures other aspects associated with governance capacity, not those directly associated with higher education. They also focus on the government’s capacity, not universities’ capacities. And although there is a distinction between these two levels, they should be somewhat related. As a set, the indicators provide a general sense of the quality contexts in which each country’s public universities are operating. This is as much as we can accomplish here.
For government capacity, a composite indicator was created from a simple average of percentile scores of WB Governance Indicators: (1) control of corruption, (2) rule of law, (3) regulatory quality, (4) government effectiveness, and (5) voice and accountability. We created a composite score of WB indicators.
The World Bank Governance Indicators were selected because as a set they represent elements likely important to University governance.
Control of corruption and rule of law address issues important to fidelity to laws and policy and the collective good, ensuring that institutional priorities are placed ahead of individual ones and that public resources are likely spent for public gains and not private ones.
Regulatory quality and government effectiveness address issues related to the quality of public sector services and regulations, the ability of governmental actors to set appropriate rules and follow them and the belief that those rules are constructive as intended, and the level of governmental credibility.
Voice and accountability are relevant because they address issues such as freedom of expression and commentary, important elements of independent higher education and because universities are public goods and should reflect collective social values and priorities.
The World Economic Forum (WEF) offers a complementary set of indicators that also may matter to public University governance. Two of WEF’s Global Competitiveness Index rankings of public sector performance and the future orientation of the government seem useful (Schwab, Reference Schwab2019).
Public sector performance addresses the ability of governments to meet their mandate without overly cumbersome regulation, similar to the World Bank’s government effectiveness variable. The future orientation of the government is important to this project because universities are a key component of creating a favorable future for the country in terms of educating the future workforce and providing inputs for the future economy of a country. How well a government looks to the future may impact its efforts related to higher education. WEF includes a corporate governance indicator, which at one point we thought might be a parallel for public governance in terms of auditing and accounting standards, conflict of interest regulation and shareholder governance, and addresses the governance ethos that exists in the country, albeit in the private sector. However, in the end, because the levers of corporate and higher education governance are different, it is not included in this analysis. For public sector effectiveness and the future orientation of government, we created percentile rankings compared to the countries in the total WEF data set. Data for Belarus, Turkmenistan, and Uzbekistan did not appear in the WEF data.
For each of the two sets of indicators we developed a percentile score for each country. This percentile score is across the whole data set, for instance across approximately 140 countries in the WEF project. We then rank ordered the 15 post-Soviet countries against each other and classified the country into quartiles – low, medium-low, medium-high, high – to parallel the autonomy assessments for rough comparison.
Because the World Bank and World Economic Forum rely on different indices, the comparative rankings of the country set differed, particularly in the middle portion of the fifteen countries. Estonia and Lithuania consistently were at the top and Kyrgyzstan was at the bottom. Belarus and Turkmenistan also scored low on WB indicators and were not included in the WEF set. Latvia ranked third in the WB indicators but dropped to sixth in the WEF set. Georgia also ranked comparatively high in the WB set at fourth but was ninth in the WEF data. Moldova was seventh comparably in the WB data but twelfth in WEF data. Russia, on the other hand, was low in WB indicators (tenth) but fifth in the WEF indicators. To iron out these differences, a simple average of averages was calculated of the two composite scores for a grand composite. Again, the analysis is not aiming for specificity as much as a general understanding of context.
These scores are unweighted and the relationships between them unexplored. Both are worthy of deeper examination, but that is beyond the scope of this chapter.
We classify level of governance capacity in quartiles as determined by their comparative percentile rankings: 100–76 as high (H); 75–51 as medium-high (MH); 50–26 as medium-low (ML); and 25 and under as low (L). See Table 19.2 for the WB, WEF, and composite assessments.
Table 19.2 Governance capacity percentile averages and comparative ranking and assessment
| Country | World Bank indicators (rank) | WEF indicators (rank) | Grand composite (rank) |
|---|---|---|---|
| Armenia | 52 (5) MH | 53 (8) MH | 53 (5) MH |
| Azerbaijan | 30 (11) ML | 67 (3) MH | 48 (7) ML |
| Belarus | 33 (9) ML | NA | NA |
| Estonia | 89 (1) H | 83 (1) H | 86 (1) H |
| Georgia | 70 (4) MH | 51 (9) MH | 60 (4) - MH |
| Kazakhstan | 43 (6) ML | 61 (4) MH | 52 (6) - MH |
| Kyrgyzstan | 27 (12) ML | 23 (13) L | 25 (13) L |
| Latvia | 78 (3) H | 54 (6) MH | 66 (3) MH |
| Lithuania | 80 (2) H | 70 (2) MH | 75 (2) MH |
| Moldova | 42 (7) ML | 37 (12) ML | 39 (9) ML |
| Russia | 32 (10) ML | 57 (5) ML | 44 (8) ML |
| Tajikistan | 10 (14) L | 47 (10) ML | 28 (12) ML |
| Turkmenistan | 5 (15) L | NA | NA |
| Ukraine | 37 (8) ML | 41(11) ML | 39 (10) ML |
| Uzbekistan | 17 (13) L | NA | NA |
These tables allow for descriptively plotting Fukuyama’s two dimensions – bureaucratic capacity and autonomy (see Figure 19.1). The figure indicates the low to high levels of autonomy and capacity given the two scales. One slope (solid line) indicates an idealized one-to-one assumed relationship that we developed for lack of clear alternatives. (See Chapter 21 for questions for further research to better explore this relationship). The second dotted line shows the relative slope across the set of the fifteen countries for a comparative understanding.
Figure 19.1 Bureaucratic capacity and autonomy by country
Figure 19.1 graphically describes the autonomy levels of the HE system and the general bureaucratic capacity in which universities operate. We wanted to create a visual summary to frame the discussion. It is not intended to demonstrate inferential analysis. Using the assumed one-to-one relationship, the capacity and autonomy of the context seem to correspond to each other well for Estonia, Lithuania, Armenia, and Turkmenistan, even though they are at different points on the slope with differing but with corresponding levels of autonomy and bureaucratic capacity. Based on the countries’ relationship to the idealized capacity-autonomy slope, Azerbaijan, Russia, Tajikistan, and Belarus seem to have bureaucratic capacity that outstrips their levels of autonomy. Inversely, Moldova, Ukraine, Latvia, and Kazakhstan seem to have greater autonomy given their levels of inferred bureaucratic capacity. Thus, to create appropriately aligned governance contexts, those countries above the solid line would need to shift to the right to increase autonomy, freeing their universities from excessive constraint. Those below the line would need to move left for lesser autonomy to align with system capacity.
Comparatively, similar but not exact patterns exist using a within-group slope: Kyrgyzstan, Ukraine, Latvia, and Moldova have autonomy levels that outpace their levels of capacity in contrast to the other countries in this set (see the dotted line in Figure 19.1). Turkmenistan, Estonia, Azerbaijan, Russia, and Tajikistan all have relative excess capacity compared to their levels of autonomy.
To what extent do the current governance structures of post-Soviet universities align with the governing contexts? Chapter 18 identified four models of University governance – academic-focused, state-extended, internal/external, and external civic. Given that policymakers are more likely to alter level of autonomy – limit it or increase it through regulatory change– as compared to have the ability to readily alter bureaucratic capacity in all of its complexity, the analysis defaults to autonomy as the potentially modified variable in this discussion.
The analysis allows one to speculate about the appropriateness of various models in different contexts. It provides a framework to speculate and raise questions, make inferences (Table 19.3).
Table 19.3 Country governance structure and capacity/autonomy levels and ratio
| Governance structure/country | Capacity/autonomy | Relationship |
|---|---|---|
| state-extended | ||
| Azerbaijan | MH/L | insufficient autonomy |
| Belarus | L/ML | insufficient autonomy |
| Russia | MH/ML | insufficient autonomy |
| Tajikistan | ML/L | insufficient autonomy |
| Turkmenistan | L/L | appropriate |
| Uzbekistan | L/L | appropriate |
| academic-focused | ||
| Georgia | MH/ML | insufficient autonomy |
| Kyrgyzstan | L/L | appropriate |
| internal/external | ||
| Armenia | MH/MH | appropriate |
| Estonia | H/H | appropriate |
| Latvia | MH/MH | appropriate |
| Lithuania | MH/MH | appropriate |
| Moldova | ML/ML | excess autonomy |
| Ukraine | ML/ML | excess autonomy |
| external civic | ||
| Kazakhstan | MH/MH | appropriate |
The state-extended models not surprisingly exist in countries with low autonomy – Azerbaijan, Belarus, Russia, Tajikistan, Turkmenistan, and Uzbekistan. However, the bureaucratic capacity levels of Azerbaijan and Russia are medium-high and that of Tajikistan and Belarus are medium-low, suggesting that each of these countries have autonomy levels that seem too low by comparison to capacity levels. The capacity of Azerbaijan seems high given the country’s government and its authoritarianism (Freedom House, Reference Donina, Meoli and Peleari2022). That may be due to the WEF indicators selected for this analysis that focus on future orientation and public sector capacity, both of which may be strong in that country’s form of political governance (Figure 19.2).
Figure 19.2 State-extended governance structures by autonomy and capacity
Turkmenistan and Uzbekistan have strongly governmentally driven University governance structures via the state-extended model that seem appropriate for the context in which those universities are operating – low capacity and low autonomy. A state-extended structure in which the government makes the most of the relevant decisions and appointments may suit those contexts well. However, for other countries, that have bureaucratic capacity that surpasses autonomy, a different University governance structure that can take advantage of capacity and autonomy may be beneficial. The state-extended model likely does not allow this, meaning that capacity goes untapped, and the system may be overly constrained by its governance approach of an extended state.
The second model, academic-focused, appears in Georgia and Kyrygstan.Footnote 1 Georgia has medium-low levels of autonomy and capacity; Kyrgyzstan is low on both dimensions. The academic-focused model suggests a level of institutional insularity – for instance, the rector is elected from within the University and the primary actors in governance are internal to the University. Two points can be inferred from the Georgia example: First, the system seems to have insufficient autonomy for its bureaucratic capacity. More autonomy may benefit its universities to act and remove some governance burden from the administration. Second, the governance structure with its insularity and focus on academic issues may align well with the comparatively low levels of autonomy but doesn’t take advantage of bureaucratic capacity. As the analysis by Dobbins and Khachatryan (Reference Dobbins and Khachatryan2015) indicate, the context has elements both of autonomy and authoritarian control. Expanding the scope and levels of autonomy and adopting a different governance model may best take advantage of capacity levels and move its institutions out of this paradoxical context. Kyrgyzstan, on the other hand, has low levels of both autonomy and capacity. It’s context more closely resembles that of the state-extended models above. Its academic focus may work against a University system that likely benefits most from close ties to the government. This model limits organization effectiveness in a low capacity, low autonomy environment; the state-extended model may yield tighter beneficial relations with the State.
The internal/external governance structures are most prevalent in countries with high and medium-high capacity and autonomy, Estonia, Latvia and Lithuania, and in Armenia with similar medium-high capacity but with a level of medium-low autonomy (see Figure 19.3). Two other countries also followed the internal/external model, Moldova and Ukraine, and they are examples of this type of governance model within medium-low autonomy and capacity. They are also the only two with dual governance structures, the second being academic-focused Academic Councils. Moldova and Ukraine are two countries in this set with seemingly excess autonomy given bureaucratic capacity. The other countries with internal/external governance models had a balanced ratio between capacity and autonomy. This model reflects the greatest variation across contexts from medium-low to high in both dimensions.
Figure 19.3 Internal/external structures by autonomy and capacity
Given that Moldova and Ukraine are countries with medium-low autonomy and capacity, the internal/external governing model may be underperforming or at least not function in ways for which the University governance structure was designed. Its bicameral governance structure means that the internal/external body, which is comprises mostly external members, is balanced with staff-dominated Academic Councils (academic-focused model). Given medium-low capacity, this may mean that the independent elements of these models may underperform; the capacity isn’t there. Concurrently, if the capacity exists, the medium-low autonomy may mean that these bodies are unable to take advantage of that autonomy to advance institutional priorities. Insights from the country profiles suggest that those with lower levels of capacity and autonomy have operational challenges of this system with undue governmental influence and in the case of Armenia a recent history of corruption (Smith & Hamilton, Reference Smith and Hamilton2015).
The three countries with the highest levels of autonomy and that also have comparatively high levels of bureaucratic capacity adopted these models of external and internal stakeholders. They may be well suited for these contexts. The governing context is different for Estonia, Latvia, and Lithuania than Ukraine and Moldova, although the University governance structures are similar. Thus, questions exist as to which context allows for effective and efficient use of a common structure and how well those structures can operate in their relative contexts? A second way to think about this difference is to consider who the stakeholders are participating in this structure. Evidence from Moldova, as well as Armenia, suggests that government actors and affiliates fill seats that can be reserved for external board members such as corporate or community leaders and educators. Thus, in medium-low autonomy contexts, the government retains a strong degree of influence through a structure that operates differently in high and medium-high autonomy contexts.
The external civic model, which in many ways is structured similarly to governing boards in the United States and United Kingdom, appears only in Kazakhstan and this is a relatively new approach for that country, with the exception of Nazarbayev University starting its second decade of operation. That country’s levels of autonomy and capacity are both medium-high but with what seems like excess levels of autonomy given bureaucratic capacity. Two potential scenarios exist. One is that the governance structure is ahead of the country’s capacities and level of granted autonomy. Thus, an external civic structure is created for a future context and having this in place may permit progress toward increased autonomy. Decision-makers are planning for a future not yet arrived and thus they will need to do the due diligence to ensure its arrival. The second possibility is that the structures, although intended to have strong external presence across a range of industries and sectors, still operates predominately or strongly with governmental influence; they are versions of state-extended models but portend to be something different. In the post-Soviet context, this may be a retrograde approach to University governance.
19.3 Making Sense of Capacity and Autonomy
This analysis across the set of fifteen former Soviet countries demonstrates a variety of governance structures situated in differing contexts. Those University systems with state-extended structures tend to be in low autonomy contexts. This is not surprising and offers confirmation that universities in low autonomy and capacity contexts may need different things from governance as compared to universities operating in other contexts. That said, based on the indicators used here, many of these countries seem to have bureaucratic capacity that outpace their levels of autonomy. This mismatch raises the question: to what extent might these universities be more efficiently, and possibly effectively, governed with a governance structure and policy schema that allowed them the autonomy to take advantage of capacity? Some countries seem to have excess bureaucratic capacity but do not leverage it and instead align University governing bodies with low levels of autonomy.
A second observation is that the internal/external model exists across a variety of capacity/autonomy levels. The similar governance structure model appears in contexts ranging from high autonomy/high capacity contexts (Lithuania) to medium-low autonomy/medium-low capacity contexts (Moldova). Unlike the state-extended structures that clustered at one end of the continuum, this model appeared across diverse contexts. This raises the question of how well these models work given their design across the capacity variations? Is there operational variation within this model depending on context? Asked another way, is there a difference between how this model works in Lithuania as compared to Moldova? We do know that Moldova adopted a different version of this model with its two parallel bodies as compared to Lithuania’s single governing body.
Relatedly, how much external voice truly exists in the internal/external structure when autonomy and capacity are low? What happens when governmental officials serve in what may be nongovernmental positions on governing boards? The critical review of Armenian University governance provides one lens into these questions (Smith & Hamilton, Reference Smith and Hamilton2015).
Third, Kazakhstan is the outlier governing structure with its external civic approach. Yet Kazakhstan’s universities seem to be operating in a medium-high autonomy and capacity context. We also know that Kazakhstan’s autonomy is a relatively new phenomenon, and the country continues to have growing pains related to it (Hartley et al., 2015). What it says on paper and in its laws may be slow to evolve in reality. This structure creates a distance from direct governance involvement and from internal stakeholders (such as academic staff). This model may better suit high-autonomy/high-capacity contexts because it allows more flexibility at the local level to pursue strategies that the University deemed valuable and have the capacity to pursue priorities that matter to the University and have less risk of inefficiency or in worse cases corruption. Because of its distance from government, the model places more responsibility and higher expectations on an independent body to act effectively and in ways that can take advantage of its context. The external civic structure also seems the model best suited for high-capacity contexts as it requires much from an independent board. The question to ask, particularly following the civil unrest in that country in winter 2022, is to what extent does the system have the needed capacity via its independent governance, or is the structure too far ahead of the policy context? And if it is ahead of the policy context is this newly adopted structure able to move the needle on autonomy and gain the needed capacity to govern well?
Implications for Policymakers and Campus Leaders
This preliminary exploration raises three implications for policymakers and campus leaders. First, a group of countries have governance structures that may be out of alignment with their autonomy and bureaucratic capacity levels. University administrators and policymakers might be well-served by exploring alternative structures to governance that allow them to take advantage of autonomy and capacity levels. If universities are not leveraging their given autonomy and capacity, they may be working inefficiently. In practical terms, universities with capacity that outpaces autonomy may be well suited for governing in a more autonomous context and thus they can make the case for increased autonomy. Russia, Azerbaijan, and Georgia might benefit from increased autonomy given the indices of bureaucratic capacity used here. However, except for Georgia with its internal/external model, the other countries noted have state-extended governance structures. Thus, in addition to making the case for increased autonomy, they might also need simultaneous reform of their governance structures, moving to less direct control and adopting the internal/external model per other more autonomous post-Soviet countries.
Second, it seems like some University systems have excess autonomy that may not be supported by their levels of bureaucratic capacity – particularly Moldova and Ukraine. The mismatch may mean that these systems do not have sufficient mechanisms in place to ensure adherence to higher education goals and priorities, might allow for universities to pursue their own priorities rather than those linked to stated educational objectives, and in worse case situations allow for corruption. Some writers have been critical of Ukrainian higher education on this point (Osipian, Reference Osipian2017, for example). Thus, these countries might be better served by constraining some levels of autonomy or putting in place safeguards to prevent poor governance. The safeguards might be differently structured governance systems and new accountability schema with clear country-level goals. The more complex undertaking is to increase the bureaucratic capacity for oversight and strategy and this too may mean new governance structures, which, for example, involving members of government or their surrogates more intentionally.
Finally, those universities in countries with high capacity and high autonomy might be better served by considering an external civic model of governance. The likely policy and governance questions focus on issues of relevance, responsiveness, and performance. Given high levels of capacity and autonomy, the compliance-focused governance approaches with less capacity is likely under delivering. One might argue that boards that are external to the University minimize stakeholder or representative conflicts of interest. As Harvard sociologist David Reisman is reported to have said, “the role of governance is to protect the future from the demands of the present” (Bowen & Tobin, Reference Bowen and Tobin2015). Thus, a broader representative stakeholder board that is external to the University may be better suited to serve as a bridge to different social and economic sectors, serve as collaborators on strategy, and balance internal decision structures. They would avoid or at least minimize representatives advocating their own positions rather than considering the good of the University as a whole (Shanahan, Reference Shanahan2019). The author’s personal experience with a representative University board in Canada suggests that University insiders dominate conversations more than external members in board meetings because they are more knowledgeable about University activities, and because they have a stronger self-interest. They also view their roles as advocating on behalf of their constituents rather than taking a broader University perspective. That said, external civic boards require the most board education because their members are not of the academy or all from the government. And effective governance via this structure does not happen naturally or easily but demands a high degree of intentionality from member selection through meeting organizations and board leadership (Chait et al., Reference Chait, Ryan and Taylor2005; Eckel & Trower, Reference Eckel and Trower2018).
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