Pressures and influences on school leaders as policy makers during COVID-19 Peter Fotheringham1 https://orcid.org/0000-0002-9247-4160, Thomas Harriott1 https://orcid.org/0000-0001-7424-9173, Grace Healy2 http://orcid.org/0000-0001-8398-1390, Gabby Arenge1 https://orcid.org/0000-0001-9619-2681, Ross McGill1 https://orcid.org/0000-0002-4993-4125, Elaine Wilson1 https://orcid.org/0000-0002-6914-7321. 1 Faculty of Education, University of Cambridge 2 UCL Institute of Education Corresponding author: Peter Fotheringham Faculty of Education, University of Cambridge 184 Hills Rd, Cambridge CB2 8PQ, United Kingdom pbff2@cam.ac.uk Abstract Pressure and influences on school leaders as school policy makers during COVID-19 have made the task of interpreting, translating and implementing guidance more a complex and essential operation. School leaders need to prioritise and balance ever-changing government policy advice, against limitations of school buildings, the welfare of students and staff as well as the needs of the communities their schools serve. By surveying and interviewing headteachers, senior leaders and governors, this paper identifies the inputs school leaders have had to react and respond to when creating policy in the context of COVID-19. The paper addresses the nature of, and factors affecting, pressures school leaders feel in authoring policy. The considerable challenges school-based policy makers face in implementing social distancing policy are non-trivial and increase tension to what is already highly stressful work. The report draws on data collected from a randomised, stratified sample of primary and secondary school leaders from across England in early June 2020, during the time of social distancing and school closure for most students. Findings suggest quality, quantity and frequency of top-down communication have contributed to school leader stress, while horizontal communication and collaboration between school leaders and across school communities helped to support leaders during rapid change. We recommend government and the education sector address communication, collaboration and change, to harness the challenges and opportunities identified by school leaders during the COVID-19 pandemic. This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3642919 Introduction / Rationale As researchers and practitioners, the authors were aware of the pressures on school systems early in the COVID-19 pandemic. Three of the authors are practising school leaders and it became clear from their own experiences that the pace and frequency of policy translation and authorship required to respond and react to the crisis has created a unique challenge. This study intends to add robust investigation to the lived experience of the authors and explore the pressures and influences on school policy writers during the COVID-19 pandemic. The COVID-19 pandemic has called for significant changes in school policy in order to comply with the government policy of social distancing implemented in England and around the world. At its peak on the 4th April 2020, social distancing closed national school systems in 194 countries, impacting 91.3% of all learners globally (UNESCO, 2020, p. 341). In many countries, school closures were announced to the public with little time allocated for consultation with school leaders, unions or education departments or professionals. National public administration offices, bureaus, ministries, government departments and agencies were charged with rapidly developing responses to guide the regional, local and municipal bodies that serve schools directly, following school closure announcements. The English case Prime Minister Boris Johnson announced school closures across England in a televised briefing on Wednesday 18th March 2020. Mr. Johnson's announcement meant that schools would end face-to-face provision of education effective Friday 22nd March 2020 (schools closed at the end of the day). The decision to close schools was informed by the Scientific Advisory Group for Emergencies ([SAGE]), a subgroup of the disaster and emergency response advisory group COBRA. A SAGE briefing note on 17th March 2020 addressed the impact of school closures for decision makers. Following the decision to close schools to most students, the DfE published guidance to be followed and interpreted by local government and individual schools.1 The magnitude of the task of timely development and enaction of policy at a school level to allow keyworker and remote education to happen is not to be underestimated. Arguably the term 'school closure' does not reflect the continued work by practitioners throughout the pandemic and that schools remained open to vulnerable children and the children of keyworkers. School leaders, faced with an average of at least three policy updates each day, were required to interpret national, local education authority (LEA) or multi-academy trust (MAT) guidance to develop policies to meet the needs of their schools' context. This paper examines the inputs leaders, as policy makers used to guide staff, students, parents/carers and the wider community within the context of the stressful and changing circumstances of the COVID-19 'lockdown'. For the purposes of this study, we understand school policies as the guidance and rules that govern school structures, staff and student behaviours and shape the culture of schools. While policy in schools in England is traditionally written by the headteachers, trials of our survey instrument indicated that 1 In England, schools are organised by county-level local government (through Local Educational Authorities or LEAs), through direct funding (either direct-to-school government Academies or groups of academies called Multi-Academy Trusts (or MATs)). There is a significant independent, fee-paying school sector (n=1390 registered with the Independent Schools Council). This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3642919 other parties are increasingly contributing to or leading policy writing. Policy makers in schools may include headteachers, executive headteachers, governors, trustees, members of senior leadership teams or business managers. Academies (unlike state-maintained schools) have some independence from LEA direction (DfE, 2012). Whilst standalone academies (single academy trusts) have greater autonomy, the majority (97%) of schools that have converted to academies joined MATs (DfE, 2016). A MAT is a single legal entity and so "individual academies may have delegated powers" (Greany & Higham, 2018, p. 15), but ultimately the trust board is accountable for all of its academies (ASCL, Browne Jacobson and NGA, 2015). Therefore, there are likely to be different inputs for school leaders working in state-maintained schools, academies that are part of standalone trusts, and academies that are part of MATs. Literature Review Interpreting and decoding, translating and applying (Ball, Maguire, & Braun, 2011) government guidance, medical advice and data is a responsibility shouldered by many school leaders. Policy creation within schools is a context-specific (A. W. Jackson & Andrews, 2000), culturally sensitive (Carey, Harris, Lee, & Aluede, 2017) exercise in a dynamic collective organisation. The development of school policy can be viewed as a shaping of power (Foucault & Morris, 1979) and leadership (Murphy & Torre, 2014) to form and deliver (Barber, Moffit, & Kihn, 2010) desired outcomes for schools. "Focus and dispersion" (Ball, 2017, p. 220) of authorship and implementation of school policy, essential for leadership, culture and organisation of schools is varied and changing and has been brought to public attention during the COVID-19 pandemic. Academic, peer reviewed literature on policy reactions to COVID-19 within social science and education journals is emerging at the time of this writing. Challenges in identifying emerging, preprint literature are considerable and we know of no certain method or process by with to gauge whether research is missing from our review. The use of the term 'unprecedented' in describing the COVID-19 pandemic has been widely commented upon, and is aptly used for the scale of the response, but as Yan (2020) notes, social distancing and school closures are part of the "traditional public health measures" (p. 1) used in response to pandemics. As such, our review examines policy responses to recent pandemics, including Ebola, SARS, MERS, and H1N1, as well as literature emerging pertaining to COVID-19. Using generalised terminology to search indexes, we determined a large set of research papers which we reduced through date-filtering and keyword identification. Like other researchers (Viner et al., 2020), examining impacts of pandemics amid crises, we identified relatively few sources directly referring to COVID-19 policy. However, the efficacy of government policy for school closure has been examined in both the present and past (Brooks, 2020; Esposito & Principi, 2020; Viner et al., 2020) contexts of viral outbreak of Influenza (De Luca et al., 2018; C. Jackson, Mangtani, Hawker, Olowokure, & Vynnycky, 2014; Mangtani, 2014; Nafisah, Alamery, Al Nafesa, Aleid, & Brazanji, 2018; Rashid et al., 2015), H1N1 (Yen et al., 2014), MERS (Cauchemez et al., 2014; Lee, Yoon, Hong, & Kim, 2015) and Ebola (Chowell & Nishiura, 2014). The World Health Organisation's (WHO) 2020 "global alert and response system for epidemics" (WHO, 2020) serves as a guide for national response, detailing appropriate responses to pandemic and so, at least in part, national policy advice responses to biosafety crises may be similar. An outbreak of Ebola Virus in 2014 in western Africa led to school closures in Sierra Leone, Liberia and Guinea on 11th June 2014. Studies of the impacts of school closures for the estimated five million students affected identified the challenges of distance learning in low-income countries (Yanoh Kay Jalloh & Raschid, 2018), the importance of communication and "collaboration with health officials and in This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3642919 consultation with community leaders and other actors such as Parent Teacher Associations (PTAs) to ease risks and fears" (Chowell & Nishiura, 2014, p. 12). The 2014 MERS policy response in South Korea called for headteachers to determine if and when schools should close ([KCDC]. 2015f). Analysis after the crisis concluded that, in instances of high transmission rates of viral infections, "closure decisions should be made at a local community level" (Lee et al., 2015). The Korean government changed responsibility for school closure from headteachers after research and feedback from 2014 MERS outbreak for regionally coordinated closure guidance (Park, 2019). The 2009 and 2014 A(H1N1) pandemics led to school closures of both a "reactive (i.e. when children or staff of the school start experiencing illness) or proactive (i.e. before substantial transmission in the school)" and included "all children and staff ("school closure") or specific classes with the remainder of the school remaining open ("class dismissal")". School closures during H1N1(2014) was national in most cases, regional in China, France and South Africa and determined at school level in Thailand and the UK (where "reactive closure of individual schools" (PHE, 2014) resulted in 74 school closures). Research on the impacts of those school closures "highlighted the difficulty in communicating in a context of uncertainty and where risk assessment may quickly change" (Cauchemez et al., 2014, p. 9). "Sporadic media criticism of rapidly changing guidance, and differences in practice between localities and over time in spite of explicit statements in the initial guidance that changes in guidance would be forthcoming pending more data", concluding that "much work remains to ensure smooth implementation of the school closure policy, a feasible NPI that may be used during future influenza pandemics" (Cauchemez et al., 2014, p. 10). Cauchemez (2014) concluded that the UK "may require a severe pandemic for (national) intervention to be considered as a policy option" (p. 8). Much like previous pandemic events, responses to COVID-19 pandemic have varied between and within countries. Vietnam, a nation with a purely state-run education system, closed schools on 1st February 2020 in line with the national Tết Nguyên Đán holiday which was extended repeatedly until schools were formally closed on 1st April 2020 (Trung et al., 2020). Despite 13 policy documents being issued during this school closure for Vietnam, some lack of information and guidance was noted by La V-P (2020), specifically, a "lack of guidelines for students as well as indecisive policies regarding school shutdowns during the early phases of the pandemic" (p. 19). The Philippines closed schools on the 16th March 2020 as part of the country's Enhanced Community Quarantine (ECQ) measures. Filipino teacher stress levels were examined during school closure and found to be heightened due to changing guidance and expectations for online learning (Talidong & Toquero, 2020). German schools were closed on 16th March 2020, "the chancellor and the federal government give general directions but policies are set at state level" (Fegert & Schulze, 2020, p. 3). In India, schools closed nationally on 25th March 2020, impacting 1.4 million schools, nearly 1000 universities 40,000 Colleges and affecting 1.3 billion Indians (Schultz, 2020). Several studies of the impacts of the closure on gender and socio-economic status groups (Bento et al., 2020). In addition to the challenges of school closure policy, distance and home learning raised concerns given that there were "no authentic directives related to the safeguarding of the schooling" (Srivastava, 2020, p. 6) from schools or the government. This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3642919 School closures in the UK were also determined on a national level, with all schools closing for most students from 20th March 2020. Schools remained open to vulnerable children ([DfE], 2020) and the children of key workers in a bid to reduce the pressure on vital services and teaching continued remotely for other students. The problems of delivering succinct, meaningful and practical guidance identified in the historic pandemic responses of countries like India, the Philippines and Vietnam helped to shape some nations' public policy response to COVID-19. The quality and timely delivery of information is essential to effective policy, especially during a pandemic characterised by widespread uncertainty and rapid change. Viner et al. (2020) concludes that "policy makers need to be aware of the equivocal evidence when proposing or implementing national or regional school closures for COVID-19"(Viner et al., 2020, p. 402), while Bento et al. (2020) find information sharing focuses "public attention on the crisis ... people seem to mainly react by seeking information on what they can and should do in response to the epidemic" (p. 7). Recommendations arising from COVID-19 research include that schools should "establish comprehensive strategies that prepare students to use e-learning" (Mailizar, Almanthari, Maulina, & Bruce, 2020, p. 8) while protecting "health and safety ... to prevent students' learning loss using remote learning ... preventing dropout, ensuring healthy school conditions, and using new techniques to promote rapid learning recovery in key areas once students are back in school" (Bank, 2020). The Lancet (2020) recommends public health policy makers "prioritise national plans for how and when to reopen schools, with consideration of alternative measures such as reduced hours or staggered lessons" (p. 341) while UNICEF (2020) also calls for staggered "mealtimes, moving classes to temporary spaces or outdoors (and) holding school in shifts, to reduce class size". The daily practices of teaching and learning and the safeguarding of children is the essential work of headteachers/principals. Hamilton, Kaufman, and Diliberti (2020) identify that 83% of principals in the USA identified providing students with direct health and education guidance as their primary responsibility. In determining policy "principals reported a need for 'strategies or resources to address the loss of students' opportunities to engage in hands-on learning (e.g., loss of internships, labs, or hands-on learning activities in the classroom).' Technology for students, training for teachers, and highquality materials to support academic instruction and social and emotional learning were also areas of relatively high need." Hamilton et al. (2020) demonstrate that "a substantial portion of teachers did not receive the guidance they needed to help all the students they served" (p. 7), leading to students with special educational needs, mild or moderate disabilities being potentially marginalised by national and regional school closure guidance. The existing literature, as well as reflections from our experiences as school leaders during COVID-19, demonstrate that the challenges faced by school leaders are varied, complicated by social concerns and infrastructure, and further complicated by unique staff and student circumstances. The responsibility for safeguarding and care of students, especially during a health crisis such as COVID-19, ultimately rests with headteachers in England schools, who must interpret, translate and implement working guidance that ensures all pupils' wellbeing and fair access to safe learning environments. The real need for rapid response and the imperative for delivering clear guidance to diverse stakeholders are significant challenges for school leaders as policy makers. Reflection on the current challenges of COVID-19 and previous challenges during past pandemics has the potential to shape support for school leaders' responses to closures, pandemics and emergencies now and in the future. This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3642919 Conceptual Framework and Context Survey rationale This paper contributes to the emerging COVID-19 educational research and reports on a survey of school-based policy makers in England to establish the value of inputs to the school policy making process. Our survey was an isolated questionnaire distributed on 15th June 2020 and closed on 20th June 2020, three months from the announcement of the COVID-19 lockdown. From the announcement of the of school to all but the children of keyworkers and vulnerable children, to the date of our survey, 201 policy updates were issued by the DfE. The results give some indication of the value school leaders as policy makers place on the government bodies and other contributors that guide and advise school policy. Respondents were subsequently randomly identified for semi-structured telephone interviews to confirm and allow for expansion on written responses; 10% of respondents (n=29) were contacted and all agreed to interview, calls were recorded and transcripts were generated and analysed to support the survey findings. All interviews took place from 20th June to 28th June 2020. Survey questions can be found in Appendix A. An anonymous online questionnaire designed in Microsoft Forms was delivered directly to school leaders via institutional email. We were interested in discovering which inputs to the policy development process school leaders took into consideration when authoring policy and guidance for their school context. The questionnaire was developed during the COVID-19 pandemic and as such was designed to be as succinct as possible, reflecting the times of high stress experienced by respondents and the authors themselves as practitioners. The questionnaire posed questions about the quantity and quality of information received by policy makers, the degree to which they felt well supported in their decision making, the nature of the challenges they faced and opportunities they perceived for creating policy in response to the COVID-19 pandemic for their schools. The intention was to develop awareness of the perceptions of school leaders, to better understand stressors for school leaders as policy makers and the processes by which policy is enacted. Inevitably, there are areas not addressed by the questionnaire which, given time, would be valuable and interesting to explore further; for example, differences in experiences between primary and secondary phases and in relation to time-in-post of leaders. However, this deliberately targeted data collection was particularly pertinent given the rapidly changing context and the motivation to elicit experiences of school policy pressures in a timely fashion, while the events of COVID-19 were still ongoing. Figure 1: Location of schools sampled This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3642919 A stratified sample of all schools in England was used to capture school types and regions separately. Drawing on the DfE school contact database and the Independent Schools Council membership list we identified a total of 24892 schools of which we anonymously survey 4951 (5% of all schools in England). We achieved an overall response rate of 6%2 of the cohort surveyed (n=298 with 10% of the survey respondents interviewed (n=29) following completion of the survey. A simplification of the DfE school classification database (see Figure 3) was used for our survey, with a table in Appendix B indicating classification processes. The DfE definition of regions was used for the research. Figure 3: School sample contacted, stratified by type Survey Sampled % of Schools by type Responses Received % of response Response rate Community School 1489 30% 93 31% 6.25% Academy Converter 941 19% 80 27% 8.50% Voluntary aided 565 11% 28 9% 4.96% Academy Sponsor Led 451 9% 9 3% 2.00% Faith school 376 8% 33 11% 8.78% N/A 353 7% 12 4% 3.13% Independent school 407 8% 23 8% 5.65% Foundation School 187 4% 12 4% 5.91% Free School 73 1% 5 2% 6.85% Further Education 109 2% 3 1% 2.75% 4951 100% 298 100% 5.98% 2 In the process of designing the survey, a sample of five headteachers tested and provided comment on the quality of questions. The survey was distributed to headteachers in two batches, a representative sample (n=98) and the full mass distribution list (n=4853). An error in the initial sample mailout revealed a researcher's workplace affiliation and a second and then third email apologising for errors was distributed. The erroneously distributed survey request received a 21.4% response rate, while the general cohort study received a response rate of 5.4%. Figure 2: Flowchart and Timeline of research This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3642919 Our study used text coding, word frequency analysis, and case-classification methods to identify themes to written-response survey questions and interview transcript data. We analysed Likert-scale responses and used statistical tools (Chronbach's Alpha, McDonald's Omega and Primary Factor Analysis (see Appendix C)) to support our investigations into relationships between responses and each policymaker's role, school type and location. BERA's (2018) Ethical Guidelines were followed to ensure that ethical risk was managed through all stages of the research. Ethical approval was gained from the Faculty of Education at the University of Cambridge and informed consent was verbally obtained from all participants. Findings: Policymaker Perceptions Perception of policy makers: Information overload School leaders' perceptions of the quantity of information they received during the COVID-19 pandemic are identified in Table 2. It is striking to see that 71% of headteachers and 77% of executive headteachers felt like they received too many inputs and too much information. In fact, as one headteacher stated in interview, they were "inundated with information, particularly at the start of the lockdown" (Interview 3), senior leaders other than headteachers more often indicated they were contented with the quantity of information provided. Information overload is far from uncommon during times of pandemic, as identified by the multinational studies earlier in this work (Fegert & Schulze, 2020; La V-P, 2020; Schultz, 2020; Talidong & Toquero, 2020), as well as previous incidents in the UK. Table 2: With regard to policy creation during COVID-19/in the past three months, I feel like I have... Just the right amount of information Not enough information to inform policy creation Too many inputs and information Total Role in the school N % of role N % of role N % of role N % of total Executive heads 1 4% 5 19% 20 77% 26 9% Governors 1 25% 2 50% 1 25% 4 1% Headteachers 30 12% 39 16% 172 71% 241 83% Deputy heads 1 6% 6 38% 9 56% 16 5% Business managers 3 75% 1 25% 0% 4 1% Total 36 12% 53 18% 202 69% 291 100% Policy development at a school level in England tends to be the responsibility of senior leadership, but is not necessarily performed by headteachers. In some cases, deputy heads, governors, or executive headteachers are the primary policy authors, and in some cases policy creation is delegated and shared within schools, trusts or local area groups. Interviews with headteachers revealed that, at least in some MATs, school policy is authored at the trust level and disseminated to schools where minor contextual adjustments are made. This changes the role played by leaders from authors to translators of policy. One headteacher of a MAT school identified a lack of decision-making power in interview as a "frustration" (Interview 12), or as one survey respondent more forcefully identified, "lack of control over (my school site) is shambolic". This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3642919 A headteacher of a school which closed in response to the 2009 H1N1 pandemic in the UK was interviewed separately from the survey respondents. In interview, the headteacher identified that school policy makers are often given too much and often changing guidance, both then as now: "one minute head teachers have been told what to do, and then the next to 'get on with the process' without the full picture and information" (Interview 7). Likert-scale responses The responses to Likert-scale questions were distributed across the range of five points from one (has not at all influenced policy development) to five (has been an essential influence on policy development). On average, the most significant inputs to productive processes were the Senior Leadership Teams (SLT) that policy makers work with (4.2/5), the DfE (4.1/5) and the UK Government (4.0/5). The least significant inputs to policy writers were individual associates not affiliated with LEAs or MATs (2.5/5), the news media (1.9/5) and social media (1.6/5) (see Figure 6). None of the respondents identified 'in-school leadership teams' as being a challenge to the development of policy, but a significant number of responses specified 'government' (n=60) and 'DfE' (n=38) as being specific challenges. The most common theme to describe the challenges faced in developing policy was 'change', which we will discuss in a separate element of this analysis. Text-response survey questions Two survey questions required text responses, the first asked policy makers to identify the "challenges faced" and the second "opportunities identified" in developing school policy under COVID-19. Challenges Response rates to the open response question "What are the main challenges you face in developing school policy under COVID?" (n=298) did not identify any significant challenges additional to those identified in the Likert-scale questions. With an average length of 25.1 words (or 159 characters), text responses often reinforced the strength of sentiments and the issues that were faced by respondents. NVivo text analysis performed on the survey text-response question "the main challenges you face in developing school policy under COVID" identified 35.4% of respondents (n=106) found that the "changing" of updates presented the most significant challenges (see Figure 4). The next most common sentiments identified were the lack of 'time' and 'clarity' in the information received. Many respondents identified challenges (N=288 or 98%) and several wrote more than 600 characters3 (n=15) in response to this question. 3 For perspective, 600 characters is exactly the length of this paragraph; 600 characters marks a 'long response', the nearest hundred length above second deviation (σ = 0.95) of the distribution of responses. Figure 4: Synonym-coded word cloud identifying challenges to policy creation This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3642919 In follow-up interviews, policy makers identified the frequency of guidance updates as a challenge to policy writing. "The element of having to keep up with all of those upgrades, as well as trying to be sure people felt I was trying to portray, you know, that things were fine, was hard" (Interview 1). "We had no period of allowance; with each wave of either press speculation, or government guidance, we had further stress" (Interview 13). Opportunities There were comparatively few opportunities identified by policy makers in response to the question what "opportunities in the processes of developing policy as a result of COVID?". Many respondents entered no comment to this question (n=105) and of those who did reply (n=192), many reported no perception of opportunities (n=51). Word-frequency analysis of responses reveal 'learning' (n=61), 'staff' (n=45) and 'development' (n=36) as the most common terms. Some respondents were optimistic in their responses, one suggesting "I think this way of learning for staff will continue post COVID": "We have developed a very successful home learning system" "The development of on-line platforms for learning and better communication with the school community especially in forcing reluctant staff to take on new technologies" "Students have really engaged (with online learning) ... We feel that this is because they feel safe in their own homes and parents/carers are grateful for all the support and input we have had with them." Survey responses were supported by interview sentiments where school leaders recognised the opportunities for staff cohesion, virtual learning professional development and remote learning, and for collaborating with the stakeholders in learning: "we just found that we had really overwhelming support from parents about what we were doing (with online learning)." (Interview 3) "everybody knows all of the (challenges) we've had to consider to come (to our solutions). It's (COVID19) brought us together" (Interview 1) Word Length Count Weighted Percentage (%) learning 8 61 3.27 staff 5 45 2.41 development 11 36 1.93 school 6 34 1.82 opportunities 13 29 1.55 online 6 28 1.50 time 4 26 1.39 working 7 24 1.29 remote 6 21 1.13 community 9 19 1.02 parents 7 19 1.02 home 4 16 1.00 Figure 5: Synonym-coded word cloud and table identifying challenges to policy creation This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3642919 Figure 6: Survey responses to the perceived significance of various inputs to the policy creation process Questions 0 1 2 3 4 5 Avg. Score 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 210 220 230 240 250 260 270 280 290 300 310 Number of respondents My senior leadership team Department of Education UK Government The staff of my organisation My students My MAT The parents of my students My LEA My governing body (or similar) Statistical data from within my organisation Trade unions Personal connections Statistical data from outside of my organis.. Professional Organisations (Societi.. Individual associates outside of organisatio.. The news media Social media 4.2 4.1 4.0 3.8 3.6 3.4 3.3 3.1 3.1 2.9 2.8 2.7 2.7 2.7 2.5 1.9 1.6 The degr.. Nil Small Somewhat Significant Essential This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3642919 Regional disparity in responses We examined sentiments of school leaders to investigate whether perceptions differed between regions, since government guidance is universally applied but may be received differently across the country (Fegert & Schulze, 2020). Some regional disparities exist in responses by policy makers. Leaders of schools in the North of England were less likely to think of government influence as essential or significant than elsewhere in the nation (see Figure 2: Perceptions of Influence of Government). The stratified sampling method used in this survey identified schools by designation and region (see Figure 3). There were a larger number of independent school responses to our survey from London than from elsewhere and more responses from faith schools in the North West than other regions, so we investigated response distribution by regions and school type and found little variation from national outcomes. Figure 7: Perceptions of Influence of Government Regional responses to the influence of the UK government and the DfE were similar and distributed across the range of responses in most regions. The influence of governing bodies was strongest in the North East region and weakest in the South East, but with little difference between regions. Leadership teams were deemed to be of essential or significant influence in nearly all schools regardless of region, community schools across the country were most likely to identify senior leadership teams as non-essential inputs. Respondents in the North East were least likely to identify students as essential or significant (39%) inputs to policy creation, while in the East Midlands they were most likely to do so (81%). The news media was deemed least essential in the North East where 0% respondents identified their input as essential or significant while in London 16% of respondents identified the contributions as important. Social media were similarly distributed throughout the regions and deemed less significant inputs than news media. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% East Midlands East of England London North East North West South East South West West Midlands Yorkshire and the Humber Nill Small Somewhat Significant Essential This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3642919 Trade union inputs into the policy creation process were least valued in the North East of England, where 10% of respondents identified their input as essential or significant while in the East of England 40% of respondents identified the contributions as important. Professional organisations contributed most to London policy making (50% of respondents identifying their inputs as significant or essential) while least contributory to policy in the North East (10%). Discussion: Communication, Collaboration, Change Communication Survey responses identified top-down communication as being the most significant challenge facing school policy makers during COVID-19. The single most frequently cited point of challenge in survey responses (n=89) and in semi-structured interviews (n=5) was difficulty in interpreting frequent policy updates from DfE and other government bodies. Respondents specifically noted the difficulty in understanding which elements of previously published government policy guidance had changes between updates. The quantity of government guidance published during this COVID-19 period is non-trivial. The DfE published fifty guidance documents specifically targeted to schools from 18th March to 18th June 2020, with eleven of those guidance notes pertaining to the day-to-day running of a school (see Figure 8). Two survey respondents independently referred to the frequency of DfE updates as 'avalanches of daily information'. Figure 8 School guidance published by DfE, https://www.gov.uk/search/guidance-and-regulation A search of the whole DfE publication database revealed that from 18th March to June 18th a total of 74 unique guidance documents were published for school policy makers. DfE guidance was updated an average of three times over the four-month period with a total of 201 policy updates issued. The frequency of these communications posed particular challenges for school leaders, with five or more policy documents published within a day ten times over the three month period (see Figure 9). 11 4 3 3 3 3 3 3 2 2 2 1 0 5 10 15 Day-to-day running of a school Changes to regulations or legislation Guidance for other providers Safe working and protective measures Special educational needs and disability (SEND) Remote education and online learning Accountability and data collections Exams and assessments Safeguarding, vulnerable children and young... Finance and administration Teacher training Residential settings Quantity of published guidance (n): This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3642919 Many survey respondents struggled to keep up with changing communication: "The differing stances in policy from central government and local government has been a nightmare. Additionally, what is guidance and what is law has caused difficulty in developing policy as schools have been implementing measures which are not necessary for example wearing gloves. Parents are still in fear and reluctant to send pupils to school" Policy makers identified opportunities to build horizontal communication in our survey. Technology, communication channels and systems for improving parent/teacher/school communication arose in survey comments (n=45). Many policy makers specifically identified collaboration software (Microsoft (n=7), Google (n=7), Zoom (n=8)) as presenting opportunities for schools, teachers, students or parents: "The part technology has played in our response app to enable quick communication with parents; use of technology for home-learning; use of Microsoft teams to support remote working & communication; on-line CPD opportunities for staff." "The importance of strong relationships and communication; the power of a website to lodge a visible record of responsive leadership and support for a large school community all stakeholders; the use of google classrooms, to engage parents as 'first teachers' of children we will definitely maintain this as part of a post-Covid school." "The use of online and virtual learning and its continuation after lock down ends. The way in which we communicate with parents has also changed for the better and parents are now more willing to engage with the school app and emails." Our research indicates that the quality of advisory content, the frequency of the release of advisory notes and the length and complexity of those notes was overwhelming to policy makers. Receiving and interpreting top-down communication was itself a challenge: processing policy advice and translating that advice into logical, meaningful school rules and guidance was ongoing and time consuming, and the process led some school leaders to feel a lack of agency. However, the data also suggests that developing means for horizontal communication within and across school communities via new digital platforms presented opportunities for school leaders to exchange localised support and collaborate with students, parents, and colleagues. Figure 9: Release date and frequency of DfE publications during COVID19 16 Mar 23 Mar 30 Mar 6 Apr 13 Apr 20 Apr 27 Apr 4 May 11 May 18 May 25 May 1 Jun 8 Jun 15 Jun 22 Jun Day of Date [2020] 0 1 2 3 4 5 6 7 8 9 10 11 Public 10 April 13 April Easter Bank Holiday 8 May 2020 Bank Holiday 24 May 2020 Bank Holiday This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3642919 Collaboration Collaboration was identified as both a challenge for organisation and an opportunity for new methods of working, during and post-COVID-19. Policy makers identified networks as being essential to their responses to COVID-19, with some MATs identified as being supportive: "Excellent collaboration with (MAT) schools across the country" "Collaboration across the ... schools in our Trust has been invaluable" One policy maker identified wrote that their MAT authored all school policy ("School policy is determined centrally by Academy Trust board and not individual schools"). MAT contributions to school policymaking identified significant regional variance in Likert scores ranging from 1 (not at all influential to policy development) to 5 (has been an essential influence on policy making) (see Figure 10). 1 2 3 4 5 East Midlands 1 2 3 4 5 East of England 0% 10% 20% 30% 40% 50% 1 2 3 4 5 London 1 2 3 4 5 North East 1 2 3 4 5 North West 0% 10% 20% 30% 40% 50% 1 2 3 4 5 South East 1 2 3 4 5 Likert scale response distribution West Midlands 0% 10% 20% 30% 40% 50% 1 2 3 4 5 Yorkshire 1 2 3 4 5 Likert scale response distribution South West Figure 10 Responses to the perceptions of influence of multi-academy trusts (see question detail in This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3642919 Policy makers voiced frustration for the challenges they faced in receiving advisory guidance from different levels and departments of government. 'Trust' and 'faith' in collaboration partners was a common theme: "Poor leadership from central government with little consideration for the time it takes to plan operational changes effectively. Now exacerbated by a total lack of trust of anything they say." "Late notice and lead in times following Govt announcements, which frequently are then contradicted when the advice papers come out from the DfE" "Information and formal guidance lags national government announcements, particularly information from LEA which has been so late as to be useless. It is quite clear that cabinet does not communicate with the DoE before making announcements leaving everyone scrabbling to develop policies in the dark while parents and students look to the College for immediate guidance." Policy makers identified opportunities in developing strong communication systems with parents and families, noting that COVID-19 helped to usher in new opportunities for building community: "Increased parental engagement with the learning of their children and increased communication between school and many parents" "Use of IT by staff to carry out home learning use of Google classrooms zoom meetings -raised competency of staff. Some vulnerable children have really benefitted from being in school within a small group of children. Staff have got to know children from other phases. Staff CPD has been an expectation for all staff e.g. completion of Skills Network Mental health of children Diploma by all staff... Good relationships have been formed with an increasing number of families the school currently delivers food parcels to 84 families. Emotional support has also been given to parents through Inclusion team and teachers on google classrooms." Frequently, schools drew on their existing local, regional, and national networks for support: "Essentially, the collegiate approach of our local learning community and our (regional) network of secondary schools has been effective for policy development." "I have worked alongside the other Head Teachers in our area so that we have a consistent approach across all our schools" This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3642919 Change The pace and scope of change were essential impacts on policy makers resulting from COVID-19. There were 133 references to 'change' in response to the question "What are the most significant challenges you face in creating policy for COVID-19?" (see Figure 11). Figure 11: Distribution of respondents identifying "change" as a challenge Change in education due to COVID-19 has affected all stakeholders in education: the government, industry, policy makers, teachers, students, parents and society at large. Policy makers voiced their struggle to meet the rapid pace of change and manage the accompanying uncertainty in our survey: "I am ... struggling with not being able to plan ahead, this isn't anyone's fault necessarily, it's a circumstance we are in, but schools are like trains, they don't change direction suddenly, it takes time." "Continual changes in Government guidance and the lack of specific direction for DfE/Government, which has created a situation where every school is doing something different and where parents and governors are using that to put pressure on individual schools to 'keep up with the Jones' in terms of what their school is able to offer, without an understanding of what each school is having to cope with." "Constant changing of information from government and DfE (at least that is how it feels). Society at large being given information at the same time as schools, so no time to put thoughts in place regarding our specific context before parents start calling." During COVID-19, emergency decision-making originated with the UK government. School leaders were discovering changes in guidance through live press conferences and mass media announcements. Decisions were being delivered with immediate or very short-term implications for schools, hospitals, transportation and other public and private services. As in other nations, news of national policy change in England was received by the public, members of the government and service providers at the same time. Unlike in the 2009 H1N1 pandemic where 0% 2% 4% 6% 8% 10% 12% 14% 16% 18% 20% Unassigned Not Applicable London West Midlands South East North West East Midlands South West East of England Yorkshire and the Hu North East Unassigned Not Applicable Free schools Academy converter Academy sponsor led Community school Voluntary aided school Faith school / Academy Foundation school Independent school Free schools alternative provision Further education Sc ho ol re gi on Percentage coverage This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3642919 Public Health England was able to give some prior warning to some heads of services and schools, COVID-19 related media updates were the vanguard of information dissemination. While policy makers were challenged by the pace, breadth and significance of change, many found the pandemic created opportunities for improvement and positive change. "There have been many positive outcomes from a new way of working and we definitely want to learn lessons moving forward and change our practice in the long term taking into account this new learning." "Many superb changes have occurred. These are 1) More flexible working practices via Microsoft teams, 2) High quality online CPD for staff, 3) Enhanced Safeguarding procedures, 4) Improving relationships with parents (these were already strong but this has made them stronger), 5) Excellent collaboration with schools across the country" The challenges and opportunities school policy makers experienced are likely to be felt by many in education and in other public and private service sectors, in the UK and throughout the world. In the current and post-COVID-19 period, significant opportunities exist to support the development of sharper communication, more effective regional, national and global collaboration and processes for managing and maximising change. Implications and Conclusions The implications of these findings are non-trivial and lead directly to actionable recommendations to government, school and other public service policy makers, MATs, LEAs and governors. Primary policy makers for schools are those individuals and groups who are ultimately responsible for the daily wellbeing and education of students. To act responsibly, policy makers require agency to create safe and productive learning environments for staff and students. During the COVID-19 crisis, the methods of dissemination of information were such that policy makers did not have adequate information to enable effective communication or confidently determine school rules and guidance for communities. The secondary impacts of this should not be underestimated, particularly in times of crisis. We identify three themes emerging from our research. Policy makers indicated opportunities for developing collaboration, change and communication through their comments in our survey and in follow-up interviews. By reflecting on the survey findings and interviews with headteachers and other school leaders, we make the following recommendations: 1. That all future updates of government policy summarise clearly identify in-line changes made and make previous iterations of policies easily accessible as references within policy documents. The low cost to government of specifying which elements of policy have changed would have a high impact on the reception, translation and understanding of policy by all consumers. 2. That policy makers be allocated time and resources and encouraged to collaborate and share their experiences outside of their regional and trust associations, where possible extending information and practical experience sharing to school leaders around the globe. We call on leadership training agencies and professional qualifications for headship to do more to establish networks of policy makers across England and abroad to 'orchestrate' (Mottram, 2020) responses. This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3642919 3. That schools, LEAs, MATs and the government measure and reflect on the effects and impacts of change and publish best practice of responses in times of crises. Responsible governance at all levels should sponsor independent inquiry into effective responses, openly and freely publishing findings to help in moving forward with education for the post-COVID-19 world and to prepare for future crises. Emergency school closures are far from uncommon and the preparedness for such events can be bettered by ensuring consistent protocol and communication systems are in place, be closures large or small in scale. The faith and goodwill of parents/carers and students, school leaders and teaching staff demands better coordinated actions, local responses and clarified communication channels. The recommendations of this paper are especially relevant for the return to 'normal' schooling: schools, parents/carers, students and the wider community should be encouraged to engage in the development of protocols and systems for safe working. The pressures and influences on school leaders as policy makers during COVID-19 are likely to be universally experienced. Clear communication and effective collaboration are essential for a managing our nations' change in response to this and future crises. This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3642919 Appendix A: Survey questionnaire and Interview prompts Pressures and influences on school policy makers in the time of Corona virus This survey assesses the inputs and pressures policy makers experience during COVID-19. Data collected will inform research in methodological policy development and lead to publication in academic journals and general news media. All responses completely confidential and anonymous. Authors are affiliated with The University of Cambridge and University College London and will abide by University data collection policies, the EU General Data Protection Regulation (GDPR) and the UK Data Protection Act 2018 (DPA 2018). 1. Identify your school region: East midlands / East of England / London / North East / North West / South East / South West / West Midlands / Yorkshire and the Humber 2. What organisation best describes your school: Academy converter / Academy sponsor led / City technology college / Community school / Faith school or academy / Foundation school / Free schools / Free schools alternative provision / Further education / Independent school / Studio schools / University technical college / Voluntarily aided schools 3. My role in the school is best described as: Executive head teacher / governor / principal or headteacher / viceor assistant or associate or deputy principal / Other 4. With regard to policy creation during COVID19/in the past three months, I feel like I have... : Too many inputs and information / Just the right amount of information / Not enough information to inform policy creation 5. In the last three months, what do you think has most influenced your school's policy development? (options were: Not at all / To a small degree / Somewhat / To a significant degree / Has been an essential influence / N/A) 6. The UK government / Department of Education / My governing body (or similar) / My senior leadership team / The staff of my organisation / My students / The parents of my students / My MAT / My LEA / Individual associates outside of organisations listed above / The news media / Social media / Trade unions / Professional organisations (societies, associations) / Personal connections / Statistical data from within my organisation / Statistical data outside of my organisation / Other 7. What are the main challenges you face in developing school policy under COVID19? 8. Have you identified opportunities in the processes of developing policy as a result of COVID? 9. Please indicate if you would like to receive a copy of your responses / a summary of all responses / any reports produced with this data 10. Please enter a correspondence email address if you indicated you wish to receive details in the question above (this address will be removed from survey results before any data analysis is performed) This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3642919 Appendix B: School type classification The Department for Education identifies 29 different school types by classification. For the purposes of our survey and sampling method, we grouped those types into ten categories. We allowed survey respondents to 'add' a school category as 'Other' in response to questionnaire and we allowed respondents to identify 'N/A' or leave no response to the question. School type Survey Sampled % of all schools by type Categorisation Community school 1286 5.17% Community School Academy converter 941 3.78% Academy Converter Voluntary aided school 565 2.27% Voluntary aided Academy sponsor led 391 1.57% Academy Sponsor Led Voluntary controlled school 376 1.51% Faith school N/A 352 1.41% N/A Other independent school 319 1.28% Independent school Foundation school 166 0.67% Foundation School Community special school 88 0.35% Community School Other independent special school 76 0.31% Independent school Local authority nursery school 69 0.28% Community School Free schools 53 0.21% Free School Pupil referral unit 46 0.18% Community School Further education 45 0.18% Further Education Academy special converter 34 0.14% Academy Sponsor Led Higher education institutions 25 0.10% Further Education Foundation special school 20 0.08% Foundation School Special post 16 institution 20 0.08% Further Education University technical college 13 0.05% Further Education Non-maintained special school 12 0.05% Independent school Academy special sponsor led 12 0.05% Academy Sponsor Led Academy alternative provision converter 12 0.05% Academy Sponsor Led Free schools special 9 0.04% Free School Free schools alternative provision 7 0.03% Free School Studio schools 4 0.02% Free School Free schools 16 to 19 4 0.02% Further Education Academy alternative provision sponsor led 2 0.01% Academy Sponsor Led Academy 16-19 converter 2 0.01% Further Education This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3642919 Appendix C: Reliability Statistic and Diagram production Diagrams used in this work were created in by importing Excel table data into Tableau (2020.1) (data was cleaned using Tableau's field assignment tools) Geographic data was derived from open source British Postal Code geolocation API postcodes.io using school postcodes from in the Department for Education schools block dataset. Chronbach's Alpha reliability scoring was completed in SPSS (v26) using the Open University procedures for data reliability calculation (http://www.open.ac.uk/socialsciences/spsstutorial/files/tutorials/cronbachs-alpha.pdf) SPSS Calculation of Chronbach's Alpha, Co-variance and reliability Item-Total Statistics Scale Mean if Deleted Scale Variance if Deleted Corrected Correlation Squared Multiple Correlation Cronbach's Alpha if Deleted UK Government 47.4667 292.76 0.488 0.862 0.909 Department of Education 47.2413 294.38 0.445 0.844 0.91 My governing body (or similar) 48.6431 293.26 0.568 0.586 0.907 My senior leadership team 47.4648 301.26 0.374 0.612 0.911 The staff of my organisation 47.7503 287.48 0.613 0.77 0.905 My students 47.9408 300.94 0.416 0.703 0.91 The parents of my students 48.2164 285.38 0.747 0.854 0.902 My MAT 48.3550 308.92 0.176 0.299 0.917 My LEA 48.8454 291.21 0.649 0.537 0.905 Individual associates outside of organisations listed above 49.1541 285.47 0.531 0.724 0.908 The news media 49.3782 260.65 0.815 0.842 0.898 Social media 49.6408 249.52 0.854 0.887 0.896 Trade unions 48.6917 281.02 0.711 0.632 0.902 Professional Organisations (Societies, Associations) 48.8273 285.39 0.581 0.661 0.906 Personal connections 48.8826 288.95 0.542 0.639 0.907 Statistical data from within my organisation 48.5662 286.24 0.689 0.579 0.903 Statistical data from outside of my organisation 48.7607 273.63 0.763 0.661 0.9 Inter-Item Covariance Matrix UK G ov ern me nt De pa rtm en t o f E du ca tio n My go ve rni ng bo dy (o r s im ilar ) My se nio r le ad ers hip te am Th e s taf f o f m y o rga nis ati on My st ud en ts Th e p are nts of m y s tud en ts My M AT My LE A Ind ivid ua l a ss oc iat es ou tsi de of org an isa tio ns lis ted ab ov e Th e n ew s m ed ia So cia l m ed ia Tra de un ion s Pr ofe ss ion al Or ga nis ati on s ( So cie tie s, As so cia tio ns ) Pe rso na l c on ne cti on s Sta tis tic al da ta fro m wit hin m y o rga nis ati on Sta tis tic al da ta fro m ou tsi de of m y org an isa tio n UK Government 1.000 0.897 0.100 0.493 0.643 0.336 0.543 0.091 0.300 -0.090 0.417 0.474 0.325 0.043 -0.035 0.218 0.382 Department of Education 0.897 1.000 0.046 0.548 0.627 0.297 0.504 0.029 0.339 -0.114 0.352 0.430 0.323 -0.014 -0.017 0.236 0.288 My governing body (or similar) 0.100 0.046 1.000 0.232 0.364 0.353 0.498 0.227 0.439 0.512 0.434 0.430 0.299 0.569 0.440 0.480 0.459 My senior leadership team 0.493 0.548 0.232 1.000 0.731 0.333 0.543 -0.101 0.292 -0.105 0.235 0.275 0.267 -0.072 0.021 0.261 0.198 The staff of my organisation 0.643 0.627 0.364 0.731 1.000 0.455 0.736 -0.022 0.431 -0.001 0.479 0.536 0.457 0.117 0.140 0.409 0.395 My students 0.336 0.297 0.353 0.333 0.455 1.000 0.712 0.263 0.174 0.073 0.268 0.223 0.204 0.199 0.001 0.338 0.323 The parents of my students 0.543 0.504 0.498 0.543 0.736 0.712 1.000 0.077 0.503 0.228 0.642 0.638 0.500 0.311 0.254 0.457 0.556 My MAT 0.091 0.029 0.227 -0.101 -0.022 0.263 0.077 1.000 0.148 0.282 0.087 0.094 0.121 0.182 0.066 0.157 0.212 My LEA 0.300 0.339 0.439 0.292 0.431 0.174 0.503 0.148 1.000 0.422 0.539 0.615 0.611 0.415 0.413 0.440 0.493 Individual associates outside of organisations listed above -0.090 -0.114 0.512 -0.105 -0.001 0.073 0.228 0.282 0.422 1.000 0.581 0.561 0.450 0.696 0.691 0.513 0.563 The news media 0.417 0.352 0.434 0.235 0.479 0.268 0.642 0.087 0.539 0.581 1.000 0.897 0.684 0.549 0.565 0.568 0.716 Social media 0.474 0.430 0.430 0.275 0.536 0.223 0.638 0.094 0.615 0.561 0.897 1.000 0.734 0.563 0.623 0.615 0.704 Trade unions 0.325 0.323 0.299 0.267 0.457 0.204 0.500 0.121 0.611 0.450 0.684 0.734 1.000 0.488 0.501 0.554 0.565 Professional Organisations (Societies, Associations) 0.043 -0.014 0.569 -0.072 0.117 0.199 0.311 0.182 0.415 0.696 0.549 0.563 0.488 1.000 0.579 0.563 0.614 Personal connections -0.035 -0.017 0.440 0.021 0.140 0.001 0.254 0.066 0.413 0.691 0.565 0.623 0.501 0.579 1.000 0.546 0.532 Statistical data from within my organisation 0.218 0.236 0.480 0.261 0.409 0.338 0.457 0.157 0.440 0.513 0.568 0.615 0.554 0.563 0.546 1.000 0.599 Statistical data from outside of my organisation 0.382 0.288 0.459 0.198 0.395 0.323 0.556 0.212 0.493 0.563 0.716 0.704 0.565 0.614 0.532 0.599 1.000 This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3642919 R (4.0.2) Calculation of McDonald's Omega, the Greatest Lower Bound, and Cronbach's alpha with confidence intervals: Observations: 83 Positive correlations: 116 out of 136 (85%) Estimates assuming interval level: Omega (total): 0.68 Omega (hierarchical): 0.53 Revelle's omega (total): 0.81 Greatest Lower Bound (GLB): 0.92 Coefficient H: 0.87 Omega (total): [0.57, 0.8] Estimates assuming ordinal level: Ordinal Omega (total): 0.62 Ordinal Omega (hierarch.): 0.46 Confidence intervals: Ordinal Omega (total): [0.5, 0.73] Using SPSS for Principle Component Analysis, we identified four components with Eigenvalues > 1: Total Variance Explained Initial Eigenvalues Rotation Sums of Squared Loadings Component Total % of Variance Cumulative % Total % of Variance Cumulative % 1 3.773 22.196 22.196 2.957 17.393 17.393 2 2.341 13.773 35.969 2.341 13.773 31.166 3 1.851 10.889 46.857 2.218 13.046 44.211 4 1.299 7.644 54.501 1.506 8.858 53.070 5 1.125 6.617 61.118 1.368 8.049 61.118 6 0.994 5.850 66.968 7 0.871 5.125 72.093 8 0.783 4.608 76.701 9 0.759 4.463 81.163 10 0.626 3.680 84.843 11 0.603 3.546 88.389 12 0.527 3.097 91.486 13 0.430 2.529 94.016 14 0.364 2.141 96.156 15 0.301 1.773 97.929 16 0.199 1.168 99.097 17 0.153 0.903 100.000 Extraction Method: Principal Component Analysis. This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=3642919 Loadings calculated using R: Corr: 0.727 Corr: 0.068 Corr: 0.035 Corr: -0.05 Corr: -0.04 Corr: 0.416 Corr: 0.152 Corr: 0.052 Corr: 0.458 Corr: 0.524 Corr: 0.260 Corr: 0.207 Corr: 0.308 Corr: 0.271 Corr: 0.424 Corr: 0.154 Corr: 0.075 Corr: 0.449 Corr: 0.389 Corr: 0.540 Corr: 0.777 Corr: 0.314 Corr: 0.263 Corr: 0.160 Corr: -0.00 Corr: 0.083 Corr: 0.257 Corr: 0.135 Corr: -0.06 Corr: 0.062 Corr: 0.248 Corr: 0.167 Corr: 0.144 Corr: 0.002 Corr: 0.141 Corr: 0.146 Corr: -0.09 Corr: -0.00 Corr: 0.254 Corr: 0.144 Corr: -0.03 Corr: -0.02 Corr: 0.009 Corr: 0.224 Corr: 0.181 Corr: 0.148 Corr: 0.056 Corr: 0.092 Corr: 0.163 Corr: 0.192 Corr: 0.160 Corr: 0.273 Corr: 0.073 Corr: -0.07 Corr: 0.206 Corr: 0.053 Corr: -0.02 Corr: 0.135 Corr: 0.065 Corr: 0.151 Corr: 0.015 Corr: 0.101 Corr: 0.201 Corr: 0.055 Corr: 0.321 Corr: 0.402 Corr: -0.06 Corr: -0.00 Corr: -0.05 Corr: 0.146 Corr: 0.159 Corr: 0.024 Corr: 0.036 Corr: 0.108 Corr: 0.254 Corr: 0.088 Corr: 0.069 Corr: 0.151 Corr: 0.126 Corr: 0.138 Corr: 0.346 Corr: 0.112 Corr: 0.145 Corr: 0.133 Corr: 0.138 Corr: 0.053 Corr: 0.132 Corr: 0.347 Corr: 0.091 Corr: 0.288 Corr: 0.144 Corr: -0.28 Corr: -0.17 Corr: 0.167 Corr: 0.078 Corr: -0.01 Corr: -0.17 Corr: -0.08 Corr: -0.06 Corr: 0.083 Corr: 0.453 Corr: 0.107 Corr: 0.397 Corr: 0.128 Corr: 0.226 Corr: -0.01 Corr: 0.101 Corr: 0.260 Corr: 0.295 Corr: 0.289 Corr: 0.253 Corr: 0.157 Corr: 0.113 Corr: 0.077 Corr: 0.219 Corr: 0.048 Corr: 0.187 Corr: 0.177 Corr: 0.297 Corr: 0.256 Corr: 0.279 Corr: 0.155 Corr: 0.183 Corr: 0.176 Corr: 0.192 Corr: 0.235 Corr: 0.252 Corr: 0.207 Corr: 0.055 Corr: 0.225 Corr: 0.210 Corr: 0.129 Corr: 0.044 Corr: 0.314 Corr: 0.139 Corr: 0.257 UKGove Departm Mygover Mysenio Thestaff Mystude Thepare MyMAT MyLEA Individua Thenew Socialm Tradeun Profess Persona Statistic Statistic U KG D ep M yg M ys The M ys The M yM M yL Indi The Soc Tra Prof Pers Stat Stat This preprint research paper has not been peer reviewed. 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