Category: Research

  • What’s driving low levels of full economic cost recovery in research?

    What’s driving low levels of full economic cost recovery in research?

    Media attention has emphasised that the financial issues facing universities continue to worsen. While research is a cornerstone and strength of the sector, it is often regarded as a cost, which leads to scrutiny as part of institutional savings targets. Despite calls to acknowledge the value of research, the focus understandably remains on research costs.

    The focus of universities on the volume and cost of unfunded research, or more accurately, internally funded research, is a question that must be addressed. Institutions are reflecting on and revising internal research allowances as part of their efforts to achieve a more sustainable financial position, as the cross-subsidy from international student fees is no longer as viable as it once was.

    The question of funded research, however, is a different matter. For quite some time, there have been questions about what constitutes the full economic cost (FEC) and how these costs are recovered when projects are funded. Both issues have once again come to the forefront in the current climate, especially as institutions are failing to recover the eligible costs of funded projects.

    As part of the Innovation & Research Caucus, an investment funded by UKRI, we have been investigating why the recovery of UKRI-funded research is often below the stated rates. To put it simply, if the official recovery rate is 80 per cent FEC, why is 80 per cent not being recovered on UKRI-funded projects?

    Understanding under-recovery

    We conducted a series of interviews with chief financial officers, pro vice chancellors for research, and directors of research services across mission groups, the Transparent Approach to Costing (TRAC) group, and various geographic regions. They identified several key reasons why universities are not recovering the funding to which they are entitled.

    Before exploring the causes of under-recovery on UKRI-funded projects, the project aimed to establish the extent to which TRAC data was curated and utilised. Notably, the study found that the data collected for TRAC does not exist within research organisations and would not otherwise be collected in this form if it were not for the TRAC reporting requirement.

    While scrutinising TRAC data was less of a priority when the financial situation was more stable, in many institutions, it is now of interest to the top table and serves as the basis for modelling, projections, and scenario planning. That said, such analysis did not always recognise TRAC’s limitations in terms of how it was compiled and, therefore, its comparability.

    In many of the research organisations consulted, the responsibilities for TRAC, project costing, and project delivery are distinct. Given the growing significance of TRAC data in influencing resource allocation and strategic decision-making, it is essential for research organisations to adopt a more integrated approach to compiling and utilising TRAC data to achieve improved outcomes.

    Drivers of under-recovery

    A wide range of factors explains why the cost recovered at the end of a funding grant is less than anticipated at the point of submission and award. Almost all respondents highlighted three factors as significant in low cost recovery:

    1. Equipment and facilities costs were consistently cited as a factor, including issues associated with allocating and costing overheads and estates. Several institutions highlighted the difficulty in realistically costing equipment and facilities shared between research projects or between research projects and teaching.
    1. Staff under-costing was frequently mentioned, as principal investigators (PIs) underestimated their own and their colleagues’ time commitment to projects. This ineffective practice was driven by a (mis)perception that lower costs will likely improve success rates – despite the emphasis being on value rather than cost within a specific funding envelope.
    2. Inflation has been identified as a factor affecting all cost elements – from staff costs related to pay settlements and promotions to the rising expenses associated with consumables, equipment, and energy. This reveals a growing gap in applications, delivery, and reporting.

    Beyond these top three, the report highlights the implications of the often “hidden” costs associated with supporting and administering UKRI grants, the perennial issues of match funding, and the often inevitable delays in starting and delivering projects – all of which add to the cost and increase the prospect of under-recovery.

    In addition, an array of other contributing factors were also raised. These included the impact of exchange rates, eligibility criteria, the capital intensity of projects, cost recovery for partners, recruitment challenges, lack of contingency, and no cost extensions. While not pinpointing the importance of a single factor, the interplay and cumulative effect were considered to result in under-recovery.

    Addressing under-recovery

    Universities bear the cost of under-recovery, but funders and universities can take several actions to improve under-recovery – some of which are low- or no-cost, could be implemented in the short term, and would make a real difference.

    Funders, such as UKRI, should provide clearer guidance for research organisations on how to cost facilities and equipment, as well as how to include these costs in research bids. Similarly, applicants and reviewers should receive clearer guidance regarding realistic expectations from PIs in leading projects, emphasising that value should be prioritised over cost. Another area that warrants clearer guidance is match funding, specifically for institutions regarding expectations and for reviewers on how match funding should be assessed. We are pleased to see that UKRI is already taking steps to address these points in its funding policies [editor’s note: this link will be live around 9am on Friday morning].

    In the medium term, research funders could also review their approaches to indexation, which could help mitigate the impact of inflation in driving under-recovery, although this is, of course, not without cost. Another area worth exploring by both research organisations and funders is the provision of shared infrastructures and assets, both within and across institutions – again, a longer-term project.

    We are already seeing institutions taking steps to manage and mitigate under-recovery, and there is scope to extend good practice. Perhaps the main challenge to improving cost recovery is better managing the link between project budgets – based on proposal costs – and project delivery costs. Ensuring a joined-up approach from project costing to reporting is important, but more important is developing a deeper understanding across these areas.

    A final point is the need to ensure that academics vying for funding really understand the new realities of cost and recovery. This has not always been the case, and arguably still is not the case. These skills – from clarifying the importance of realistic staff costs to accurately costing the use of facilities to effectively managing project budgets – will help close the cost recovery gap.

    The real FEC of research funding

    The current project has focused on under-recovery in project delivery. The next step is to understand the real cost to research organisations of UKRI grant funding.

    This means understanding the cost of developing, preparing and submitting a UKRI grant application – whether successful or not. It means understanding the costs associated with administering and reporting on a UKRI grant during and beyond the life of a project (think ResearchFish!).

    For more information, please get in touch – or watch this space for further findings.

    The Innovation & Research Caucus report, Understanding low levels of FEC cost recovery on UKRI grants, will be published on the UKRI site later today.

    Source link

  • Research funding won’t redistribute itself

    Research funding won’t redistribute itself

    On the whole research funding is not configured to be sensitive to place.

    Redistribution

    It does good things in regions but this is different to funding being configured to do so. For example, universities in the North East performed strongly in the REF and as a consequence they received an uplift in QR funding. This will allow them to invest in their research capacity, this will bring agglomerate benefits in the North East, and go some small way to rebalancing the UK’s research ecosystem away from London.

    REF isn’t designed to do that. It has absolutely no interest where research takes place, just that the research that takes place is excellent. The UK isn’t a very big place and it has a large number of universities. Eventually, if you fund enough things in enough places you will eventually help support regional clusters of excellence.

    There are of course some specific place based funds but this doesn’t mean they are redistributive as well as being regionally focussed. The Higher Education Innovation Fund (HEIF) is focussed on regional capacity but it is £260m of a total annual Research England funding distribution of £2.8bn. HEIF is calculated using provider knowledge exchange work on businesses, public and third sector engagement, and the wider public. A large portion of the data is gathered through the HE-BCI Survey.

    The result of this is that there is place based funding but inevitably institutions with larger research capacities receive larger amounts of funding. Of the providers that received the maximum HEIF funding in 2024/25 five were within the golden triangle, one was in the West Midlands, one was in the East Midlands, two were in Yorkshire and the Humber, one was in the North West, and one was in the South East but not the golden triangle. It is regional but it is not redistributive.

    Strength of feeling/strength in places

    RAND Europe has released a process evaluation of wave two of the Strength in Places Fund (SIPF). As RAND Europe describe the fund is

    The Strength in Places Fund (SIPF) is a £312.5 million competitive funding scheme that takes a place-based approach to research and innovation (R&I) funding. SIPF is a UK Research and Innovation (UKRI) strategic fund managed by the SIPF delivery team based at Innovate UK and Research England. The aim of the Fund is to help areas of the UK build on existing strengths in R&I to deliver benefits for their local economy

    This fund has been more successful in achieving a more regionally distributed spread of funding. For example, the fund has delivered £47m to Wales compared to only £18m in South East England. Although quality was a key factor, and there are some challenges to how aligned projects are to wider regional priorities, it seems that a focus on a balanced portfolio made a difference. As RAND Europe note

    […]steps were taken to ensure a balanced portfolio in terms of geographical spread and sectors; however, quality was the primary factor influencing panel recommendations (INTXX). Panel members considered the projects that had been funded in Wave 1 and the bids submitted in Wave 2, and were keen on ensuring no one region was overrepresented. One interviewee mentioned that geographical variation of awards contributed to the credibility of a place-based funding system[…].

    The Regional Innovation Fund which aimed to support local innovation capacity was allocated with a specific modifier to account for where there had historically been less research investment. SPIF has been a different approach to solving the same conundrum of how best support research potential in every region of the UK.

    It’s within this context that it is interesting to arrive at UKRI’s most recent analysis of the geographical distribution of its funding in 2022/23 and 2023/24. There are two key messages the first is that

    All regions and nations received an increase in UKRI investment between the financial years 2021 to 2022 and 2023 to 2024. The greatest absolute increases in investment were seen in the North West, West Midlands and East Midlands. The greatest proportional increases were seen in Northern Ireland, the East Midlands and North West.

    And the second is that

    The percentage of UKRI funding invested outside London, the South East and East of England, collectively known as the ‘Greater South East’, rose to 50% in 2023 to 2024. This is up from 49% in the 2022 to 2023 financial year and 47% in the 2021 to 2022 financial year. This represents a cumulative additional £1.4 billion invested outside the Greater South East since the 2021 to 2022 financial year.

    Waterloo sunset?

    In the most literal sense the funding between the Greater South East and the rest of the country could not be more finely balanced. In flat cash terms the rest of the UK outside of the Greater South East has overtaken the Greater South East for the first time while investment per capita in the Greater South East still outstrips the rest of the country by a significant amount.

    The reasons for this shift is because of greater investments in the North West, West Midlands, and East Midlands who cumulatively saw an increase of £550m worth of funding over the past three years. The regions with the highest absolute levels of funding saw some of the smallest proportions of increases in investment.

    The evaluations and UKRI’s dataset present an interesting picture. There is nothing unusual about the way funding is distributed as it follows where the highest numbers of researchers, providers, and economic activity is located. It would be an entirely arbitrary mechanism which penalised the South East for having research strengths.

    Simultaneously, with constrained resources there are lots of latent assets outside of the golden triangle that will not get funding. The UK is unusually reliant on its capital as an economic contributor and research funding follows this. The only way to rebalance this is to make deliberate efforts, like with SIPF, to lean toward a more balanced portfolio of funding.

    This isn’t a plea to completely rip up the rule book, and a plea for more money in an era of fiscal constraint will not be listened to, but it does bring into sharp relief a choice. Either research policy is about bolstering the UK’s economic centre or it is about strengthening the potential of research where it receives less funding. There simply is not enough money to do both.

    Source link

  • Trump: Aus research must disclose vaccine, transgender, DEI or China ties

    Trump: Aus research must disclose vaccine, transgender, DEI or China ties

    US President Donald Trump in the Oval Office of the White House. Picture: Mandel Ngan



    By: Erin Morley

    in Industry & Research, Research Funding, Research News, Top Stories


    March 17, 2025

    Australian researchers who receive United States funding have been asked to disclose links to China and whether they agree with US President Donald Trump’s “two sexes” executive order.

    Please login below to view content or subscribe now.

    Membership Login

    Source link

  • Three Ways Faculty Are Using AI to Lighten Their Professional Load

    Three Ways Faculty Are Using AI to Lighten Their Professional Load

    Reading Time: 4 minutes

    Our most recent research into the working lives of faculty gave us some interesting takeaways about higher education’s relationship with AI. While every faculty member’s thoughts about AI differ and no two experiences are the same, the general trend we’ve seen is that faculty have moved from fear to acceptance. A good deal of faculty were initially concerned about AI’s arrival on campus. This concern was amplified by a perceived rise in AI-enabled cheating and plagiarism among students. Despite that, many faculty have come to accept that AI is here to stay. Some have developed working strategies to ensure that they and their students know the boundaries of AI usage in the classroom.

    Early-adopting educators aren’t just navigating around AI. They have embraced and integrated it into their working lives. Some have learned to use AI tools to save time and make their working lives easier. In fact, over half of instructors reported that they wanted to use AI for administrative tasks and 10% were already doing so. (Find the highlights here.) As more faculty are seeing the potential in AI, that number has likely risen. So, in what ways are faculty already using AI to lighten the load of professional life? Here are three use-cases we learned about from education professionals:

    1. AI to jumpstart ideas and conversations

    “Give me a list of 10 German pop songs that contain irregular verbs.”

    “Summarize the five most contentious legal battles happening in U.S. media law today.”

    “Create a set of flashcards that review the diagnostic procedure and standard treatment protocol for asthma.”

    The possibilities (and the prompts!) are endless. AI is well-placed to assist with idea generation, conversation-starters and lesson materials for educators on any topic. It’s worth noting that AI tends to prove most helpful as a starting point for teaching and learning fodder, rather than for providing fully-baked responses and ideas. Those who expect the latter may be disappointed, as the quality of AI results can vary widely depending on the topic. Educators can and should, of course, always be the final determinants and reviewers of the accuracy of anything shared in class.

    1. AI to differentiate instruction

    Faculty have told us that they spend a hefty proportion (around 28%) of their time on course preparation. Differentiating instruction for the various learning styles and levels in any given class constitutes a big part of that prep work. A particular lesson may land well with a struggling student, but might feel monotonous for an advanced student who has already mastered the material. To that end, some faculty are using AI to readily differentiate lesson plans. For example, an English literature instructor might enter a prompt like, “I need two versions of a lesson plan about ‘The Canterbury Tales;’ one for fluent English speakers and one for emergent English speakers.” This simple step can save faculty hours of manual lesson plan differentiation.

    An instructor in Kansas shared with Cengage their plans to let AI help in this area, “I plan to use AI to evaluate students’ knowledge levels and learning abilities and create personalized training content. For example, AI will assess all the students at the beginning of the semester and divide them into ‘math-strong’ and ‘math-weak’ groups based on their mathematical aptitude, and then automatically assign math-related materials, readings and lecture notes to help the ‘math-weak’ students.”

    When used in this way, AI can be a powerful tool that gives students of all backgrounds an equal edge in understanding and retaining difficult information.

    1. AI to provide feedback

    Reviewing the work of dozens or hundreds of students and finding common threads and weak spots is tedious work, and seems an obvious area for a little algorithmic assistance.

    Again, faculty should remain in control of the feedback they provide to students. After all, students fully expect faculty members to review and critique their work authentically. However, using AI to more deeply understand areas where a student’s logic may be consistently flawed, or types of work on which they repeatedly make mistakes, can be a game-changer, both for educators and students.

    An instructor in Iowa told Cengage, “I don’t want to automate my feedback completely, but having AI suggest areas of exigence in students’ work, or supply me with feedback options based on my own past feedback, could be useful.”

    Some faculty may even choose to have students ask AI for feedback themselves as part of a critical thinking or review exercise. Ethan and Lilach Mollick of the Wharton School of the University of Pennsylvania share in an Harvard Business Publishing Education article, “Though AI-generated feedback cannot replicate the grounded knowledge that teachers have about their students, it can be given quickly and at scale and it can help students consider their work from an outside perspective. Students can then evaluate the feedback, decide what they want to incorporate, and continue to iterate on their drafts.”

    AI is not a “fix-all” for the administrative side of higher education. However, many faculty members are gaining an advantage and getting some time back by using it as something of a virtual assistant.

     

    Are you using AI in the classroom?

    In a future piece, we’ll share 3 more ways in which faculty are using AI to make their working lives easier. In the meantime, you can fully explore our research here:

     

     

     

    Source link

  • Trust, creativity, and collaboration are what leads to impact in the arts

    Trust, creativity, and collaboration are what leads to impact in the arts

    Impact in the arts is fundamentally different from other fields. It is built on relationships, trust, and long-term engagement with communities, businesses, and cultural institutions.

    Unlike traditional research models, where success is often measured through large-scale returns or policy influence, impact in the creative industries is deeply personal, embedded in real-world collaborations, and evolves over time.

    For specialist arts institutions, impact is not just about knowledge transfer – it’s about experimental knowledge exchange. It emerges from years of conversations, interdisciplinary convergence, and shared ambitions. This process is not transactional; it is about growing networks, fostering trust, and developing meaningful partnerships that bridge creative research with industry and society.

    The AHRC Impact Acceleration Account (IAA) has provided a vital framework for this work, but to fully unlock the potential of arts-led innovation, it needs to be bigger, bolder, and more flexible. The arts sector thrives on adaptability, yet traditional funding structures often fail to reflect the reality of how embedded impact happens – rarely immediate or linear.

    At the University for the Creative Arts (UCA), we have explored a new model of knowledge exchange—one that moves beyond transactional partnerships to create impact at the convergence of arts, business, culture, and technology.

    From ideas to impact

    At UCA, IAA impact has grown not through top-down frameworks, but through years of relationship-building with creative businesses, independent artists, cultural organisations, and museums. These partnerships are built on trust, long-term engagement, and shared creative exploration, rather than short-term funding cycles.

    Creative industries evolve through conversation, experimentation, and shared risk-taking. Artists, designers, filmmakers, and cultural institutions need time to test ideas, adapt, and develop new ways of working that blend creative practice with commercial and social impact.

    This approach has led to collaborations that demonstrate how arts impact happens in real-time, to name a few:

    • Immersive storytelling and business models – Research in VR and interactive media is expanding the possibilities of digital storytelling, enabling new audience experiences and sustainable commercial frameworks for creative content.
    • Augmented reality and cultural heritage – Digital innovation is enhancing cultural engagement, creating interactive heritage experiences that bridge physical and virtual worlds, reinforcing cultural sustainability.
    • Sustainable design and material innovation – Design-led projects are exploring circular economy approaches in sports, fashion, and product design, shifting industry mindsets toward sustainability and responsible production.
    • Photography and social change – Research in archival and curatorial practice is reshaping how marginalised communities are represented in national collections, influencing curatorial strategies and institutional policies.

    These projects are creative interventions that converge research, industry, and social change. We don’t just measure impact; we create it through action.

    A different model of knowledge exchange

    The AHRC IAA has provided an important platform for arts-led impact, but if we are serious about supporting creative industries as a driver of economic, cultural, and social transformation, we must rethink how impact is funded and measured. Traditional funding models often overlook the long-term, embedded collaborations that define arts impact.

    To make the impact funding more effective, we need to:

    • Recognise that creative impact develops over time, often requiring years of conversation, trust-building, and iterative development.
    • Encourage risk-taking and experimentation, allowing researchers and industry partners the flexibility to develop innovative ideas beyond rigid funding categories.
    • Expand the scale and duration of support to enable long-term transformation, allowing small and specialist universities to cultivate deeper, sustained partnerships.

    In academic teaching and training, knowledge exchange must be reconsidered beyond the REF framework. Rather than focusing solely on individual research outputs, assessment frameworks should value collective impact, long-term partnerships, and iterative creative inquiry. Funding models should support infrastructure that enables researchers to develop skills in knowledge exchange, ensuring it is a fundamental pillar of academic and professional growth.

    By embedding knowledge exchange principles into creative education, we can cultivate a new generation of researchers who are not only scholars but also creative change makers, equipped to collaborate with industry, drive cultural innovation, and shape the future of the creative economy.

    A call for bigger, bolder AHRC impact funding

    UCA’s approach demonstrates how arts institutions are developing a new model of impact—one rooted in collaboration, creativity, and social change. However, for this model to thrive, impact funding must evolve to recognise and support the unique ways in which creative research generates real change.

    To keep pace with the evolving needs of cultural, creative, and technology industries, research funding must acknowledge that impact in the arts is about stories, communities, and the human connections that drive transformation. It’s time to expand our vision of what impact means – and to build a funding model that reflects the true value of the arts in shaping business, culture, and society.

    Source link

  • AI Support for Teachers

    AI Support for Teachers

    Collaborative Classroom, a leading nonprofit publisher of K–12 instructional materials, announces the publication of SIPPS, a systematic decoding program. Now in a new fifth edition, this research-based program accelerates mastery of vital foundational reading skills for both new and striving readers.

    Twenty-Five Years of Transforming Literacy Outcomes

    “As educators, we know the ability to read proficiently is one of the strongest predictors of academic and life success,” said Kelly Stuart, President and CEO of Collaborative Classroom. “Third-party studies have proven the power of SIPPS. This program has a 25-year track record of transforming literacy outcomes for students of all ages, whether they are kindergarteners learning to read or high schoolers struggling with persistent gaps in their foundational skills.

    “By accelerating students’ mastery of foundational skills and empowering teachers with the tools and learning to deliver effective, evidence-aligned instruction, SIPPS makes a lasting impact.”

    What Makes SIPPS Effective?

    Aligned with the science of reading, SIPPS provides explicit, systematic instruction in phonological awareness, spelling-sound correspondences, and high-frequency words. 

    Through differentiated small-group instruction tailored to students’ specific needs, SIPPS ensures every student receives the necessary targeted support—making the most of every instructional minute—to achieve grade-level reading success.

    “SIPPS is uniquely effective because it accelerates foundational skills through its mastery-based and small-group targeted instructional design,” said Linda Diamond, author of the Teaching Reading Sourcebook. “Grounded in the research on explicit instruction, SIPPS provides ample practice, active engagement, and frequent response opportunities, all validated as essential for initial learning and retention of learning.”

    Personalized, AI-Powered Teacher Support

    Educators using SIPPS Fifth Edition have access to a brand-new feature: immediate, personalized responses to their implementation questions with CC AI Assistant, a generative AI-powered chatbot.

    Exclusively trained on Collaborative Classroom’s intellectual content and proprietary program data, CC AI Assistant provides accurate, reliable information for educators.

    Other Key Features of SIPPS, Fifth Edition

    • Tailored Placement and Progress Assessments: A quick, 3–8 minute placement assessment ensures each student starts exactly at their point of instructional need. Ongoing assessments help monitor progress, adjust pacing, and support grouping decisions.
    • Differentiated Small-Group Instruction: SIPPS maximizes instructional time by focusing on small groups of students with similar needs, ensuring targeted, effective teaching.
    • Supportive of Multilingual Learners: Best practices in multilingual learner (ML) instruction and English language development strategies are integrated into the design of SIPPS.
    • Engaging and Effective for Older Readers: SIPPS Plus and SIPPS Challenge Level are specifically designed for students in grades 4–12, offering age-appropriate texts and instruction to close lingering foundational skill gaps.
    • Multimodal Supports: Integrated visual, auditory, and kinesthetic-tactile strategies help all learners, including multilingual students.
    • Flexible, Adaptable, and Easy to Teach: Highly supportive for teachers, tutors, and other adults working in classrooms and expanded learning settings, SIPPS is easy to implement well. A wraparound system of professional learning support ensures success for every implementer.

    Accelerating Reading Success for Students of All Ages

    In small-group settings, students actively engage in routines that reinforce phonics and decoding strategies, practice with aligned texts, and receive immediate feedback—all of which contribute to measurable gains.

    “With SIPPS, students get the tools needed to read, write, and understand text that’s tailored to their specific abilities,” said Desiree Torres, ENL teacher and 6th Grade Team Lead at Dr. Richard Izquierdo Health and Science Charter School in New York. “The boost to their self-esteem when we conference about their exam results is priceless. Each and every student improves with the SIPPS program.” 

    Kevin Hogan
    Latest posts by Kevin Hogan (see all)

    Source link

  • How R&D creates new skills and can jump start the economy

    How R&D creates new skills and can jump start the economy

    Skills England, the government’s new-ish arms length body exists to coordinate the work of employers, educators, and civic leaders to meet the skills needs of the country over the next decade. As the Secretary of State for Education states in the opening of Skill’s England’s inaugural report

    The first mission of this government is economic growth. Central to this mission is a skills system fit for the future. We need to harness the talents of all our people to unlock growth and break down the barriers to opportunity. Each and every young person and adult in the country must be able to learn the skills they need to seize opportunity. Businesses need a highly skilled workforce to draw on if they are to drive economic growth and expand opportunity in our communities.

    On the face of it the argument is compelling. The mission is to have a bigger economy. The method is to increase economic output in key industries. The means is to have people to deliver those outputs. And the result is a more productive economy and a rise in living standards.

    One of the challenges the government faces is that it has a limited set of tools. It can set incentives and regulation but in mass swathes of the economy it cannot set wages, tell businesses what to do, and for more than a decade no government has made the country significantly more productive.

    As the National Centre Institute of Economic and and Social Research argues one of the reasons the UK’s productivity is stuck is because the uneven distribution of skills also leads to the uneven distribution of clusters that can spin up economic activity. Plainly, if the country keeps producing similar graduates with similar skills the economy will end up in a similar place. It might not be just that we are training the wrong skills but that we’re thinking about graduate skills entirely wrongly.

    Supply and demand

    It is quite hard to work out what skills will free the country from its productivity trap.

    For example, the Department for Education provides a bulletin on occupations in demand and it makes for mixed reading for universities.

    82.5 per cent of the occupations which the Department believes are in critical demand do not require a degree level education. Critical demand is a composite measure which assesses outliers against seven indicators which “include the number of visa applications, online job adverts and annual wage growth.” The most critically in demand occupation is care work, followed by sales accounts and business development managers, and then metal working production and maintenance fitters.

    To be clear, this is a different analysis on whether those occupations benefit from someone having a degree in them. If you take a profession like childcare there are zero barriers to entry, zero licensing requirements, and in the informal childcare sector zero need for background checks. All things being equal, having nannies trained somewhere like Norland which produces highly qualified nannies is a net good for children and the economy.

    The professions that are the highest in demand do not require a university degree. Therefore, there is an argument that reducing the number of people with a university degree would not harm the economy overall. A version of this narrative is played out in the too many people go to university debate and the UK needs more apprentices debate. Whether either of these things are true, having more apprentices would seem to be a good thing, they don’t always consider how universities themselves create demand for new skills in the workforce.

    To put it plainly, universities don’t just supply skills, they create demand for them.

    Alignment

    This is because universities carry out research and one of the core purposes of research is to create products and services that can be adopted into the real economy.

    The social and political implications of the contraceptive pill, the media campaigns to reduce smoking, and the innovation in materials arising from the motorway signs developed at the Royal School of Art, demonstrate R&D from UK universities shapes the skills society needs in an unexpected way.

    This is a different kind of shaping of the skills landscape than the government. The government’s approach is top down: putting in place incentives, regulations, and investment, to create a different kind of labour market. Universities work from the bottom up by pursuing things that are interesting, turning ideas into reality, and then creating new kinds of work. This work then has to be serviced by new skills and new combinations of existing skills.

    Kate Black, the co-founder of University of Liverpool spin-out Meta Additive, couches her work in similar terms:

    It is amazing to be able to take my research which started life in a laboratory at the University and then translate it into the real-world, helping to create jobs and providing industry with smart manufacturing solutions.

    There are new skills and new kinds of work needed because of the work of universities. Clearly, it’s harder to predict the industries that are yet to emerge.

    Narratives

    Student fees cross subsidise research but this does not mean there is a good relationship between which students universities recruit and what research they should fund. This has led to the current arrangements where incentives encourage a broad programme mix, in turn encouraging a growth in student numbers, therefore requiring academics to teach students, and in part creating research across a broad portfolio. The incentives for funding research works against specialisation for the majority of institutions.

    This leads to a skills system that is led by student demand for places not the skills an economy needs. In turn, this limits the kind of research that takes place, which in turn limits the creation of new demand for skills.

    For example, Labour’s industrial strategy requires a workforce skilled in core sciences. The university recruitment landscape is working against having more people taking up those roles. The more numbers decline, the less likely universities are to provide those courses, and the more the UK’s R&D base will suffer, which will limit the creation of new jobs and demand for skills to fulfill them.

    This leaves an enormous policy conundrum. One option would be to designate programmes of critical importance which are allowed a permanent funding settlement to support R&D and skills development. This could be an increase in the teaching grant or additional hypothecated funding through the research councils. This would help the stability of the R&D and skills pipeline but it would be massively unpopular for some institutions, hasten the closure of non critical research fields, and it does not solve the problem that skills and research needs are unpredictable.

    The other solution is a more stable research funding settlement for universities that nudges toward de-coupling research funding from student recruitment. This would mean either more research funding to maintain the current system or fewer better funded projects. Again, not easy or cheap.

    Universities will respond to the incentives in front of them but the narrative is theirs to shape. Instead of talking about research, graduate jobs, and a graduate skills gap, the opportunity is to talk about how the economy really works. The current arrangement incentivises universities to continually tack their programmes, research, and offer to the funding in front of them. An alternative narrative is the investment in broad based curricula and research is the best insurance against an economy which is unpredictable, and the only opportunity to jump start an economy which is comatose. This requires long-term and predictable funding.

    Source link

  • Research flexibility doesn’t have to mean researcher precarity

    Research flexibility doesn’t have to mean researcher precarity

    If we think about research as a means of driving innovation and by extension economic growth, there is a need to consider the lives of the people who are doing the research.

    The UK has a significant strength in the quality and diversity of its higher education system – which trains a large proportion of the staff who end up working in universities (and elsewhere) performing research. We should, in other words, be better than we are at sustaining and shaping research capacity through supporting the people who contribute research throughout their careers.

    Certainly, that’s the case that the University and College Union makes in last week’s research staff manifesto – noting that nearly two thirds of research staff are on fixed term contracts, following research funding and strategic decisions around the country at a significant detriment to their personal lives and professional development.

    How does the system work?

    Precarity is not an accident of the system – it is the entire design of the system. Becoming a postdoc is not the final stage of the undergraduate to postgraduate to researcher pipeline: it is a step into a new system where the trial of job-hopping, house moving, city shifting work, may one day lead to a full time post.

    The first step after undertaking a doctorate is, unsurprisingly post-doctoral work – the postdoc. The term is confusing as it implies simply the job someone does after being awarded a PhD. Over time the taxonomy has changed to take on a specific meaning. It has become synonymous with precarious employment tied to grant funding. As an example, Imperial College London describes their postdocs as follows

    • a member of staff who will have a PhD, and be employed to undertake research
    • commonly on an externally funded grant secured by their principal investigator (PI) e.g. Research Council standard grant
    • responsible for their own career development but entitled to the support of their PI and the PFDC
    • entitled to 10 days development per year
    • entitled to 25 days leave plus bank holidays and college closure dates (if full time, pro-rata for part time)
    • entitled to regular one-to-one meetings with their line manager
    • entitled to a mid and final probation review
    • entitled to a Personal Review and Development Plan (PRDP) meeting once per year

    Crucially, in the section which describes what a postdoc is not, it includes being “a permanent member of academic staff.”

    This is often the case because postdocs are tied to grant funding and grant funding is limited to a certain period of time to cover a specific project. UKRI, for example, does not fund postdocs directly but funds research organisations directly through a mix of focused studentships and capacity funding. Research organisations then fund postdocs.

    This means that the flexible deployment of resources is the very start of the system. It’s not an accident or a quirk, it is that the UK’s research system is built around incentivising human capital to move to the organisations and places that most closely aligns to their research skills. The upside of this is that, in theory, it should mean resources are efficiently deployed to the people and places that can use them most productively. In reality, it means that instability and structural barriers to progressing to full research contracts are the norm.

    It’s not that UKRI are not aware of this problem. In a 2023 blog on team research Nik Ogryzko, Talent Programme Manager at UKRI, wrote that

    We’ve built a system where research groups sometimes act as their own small business inside an institution. And this leads to a very particular set of weaknesses.

    Employment contracts have become linked to individual research grants, with research staff often highly dependent on their principal investigator for career progression, or even their continued employment.

    Group leaders are often not equipped to support their staff into anything other than an academic career, and we know most research staff do not end up there.

    We also know such precarious employment and power imbalances can in some cases lead to bullying, harassment and discrimination. Such structural factors further compromise the integrity of our research, despite the strong intrinsic motivation of our researchers and innovators.“

    A number of institutions are signatories to The Concordat to Support the Career Development of Researchers. When it comes to the use of fixed-term contracts the concordat states that

    […]some of the areas of most concern to researchers, such as the prevalence of fixed-term contracts and enforced mobility, will require long term systemic changes, which can only be realised through collective action across stakeholders.

    Again, should a researcher be lucky enough to pass through their postdoc a permanent role is not guaranteed or even the norm. In reading through the websites of universities the reasons for fixed term contracts are various including; to align with grant-funding, to cover peak demand, to meet uncertain demand, to cover staff absence, to cover time-limited projects, secondments, training, and to bring in specialist skills.

    It is not that universities don’t recognise the issue of fixed term contracts, institutions like the University of Exeter has a whole framework on the appropriate use of these contacts, it’s that in a funding system which places a premium on project working it is necessary to have a highly flexible staff force.

    However, this does not mean that this system is inevitable or that the number of fixed term contracts is desirable.

    What is going on?

    According to HESA data, that number is slowly falling – both numerically and proportionally – for research only academic staff. As of the 2023-24 academic year, 63.9 per cent of “research only” academic staff (64,265) are on a fixed term contract. This sounds like a lot, but it is down slightly from a peak of 68 per cent (70,050) in 2019-20.

    [Full screen]

    The proportion of fixed term contracts for teaching only academics (another prominent early career route, often coupled with weekends at the kitchen table writing literature reviews for publication in an attempt to bolster credentials for a research job in an underfunded field) is also on a downward trajectory. Some 44.3 per cent of teaching only contracts (equating to 64,300 people) were fixed term in 2019-20 – by 2023-24 the numbers were 35.7 per cent and 63,425.

    If we take this to provider level we can see that a significant research focus is no predictor of a reliance on fixed term contracts. This chart shows the proportion of all academic staff on research only contracts on the y axis, with the proportion of all academic staff on fixed term contracts on the x axis.

    [Full screen]

    What this chart shows is that a strong focus on research (with many research only academic contracts) does not predict a reliance on fixed term contracts – indeed, there are many providers with a significant proportion of fixed term contracts that have no research only academic staff at all. While a fixed term contract is a poor basis on which to plan long term as an individual, for many higher education institutions it is a useful answer to wildly varying income and recruitment. Whereas for more traditional institutions it makes sense to maintain capacity even as prevailing conditions worsen, in smaller and more precarious providers unutilised capacity is a luxury that is no longer as affordable.

    If you look back to the first chart, you may notice a “salary source” filter. One of the prevailing narratives around fixed term contracts is that these necessarily link to the “fixed term” nature of funded research projects – the argument being that once the money is finished, the staff need to find new jobs. In fact, this is less of a factor than you might imagine: the proportions of research only academic staff on fixed term contracts is higher for externally funded than those funded internally, but the difference isn’t huge.

    Plotting the same data another way shows us that around a quarter of research only salaries are funded entirely by the higher education provider, with a further five per cent or so partially supported by the host institution – these figures are slightly lower for fixed-term research only staff, but only very slightly.

    [Full screen]

    So we can be clear that fixed term salaries are (broadly) a research thing, but there’s not really evidence to suggest that short term external funding is the whole reason for this.

    As a quick reminder, the research councils represent about a quarter of all external research funding, with the UK government (in various forms) and the NHS representing about another (swiftly growing)fifth. That’s a hefty chunk of research income that comes from sources that the government has some degree of control over – and some of the language used by Labour before the election about making this more reliable (the ten year settlements of legend) was seen as a recognition of the way funding could be reprofiled to allow for more “livable” research careers and an expansion of research capacity.

    [Full screen]

    This chart also allows you to examine the way these proportions land differently by provider and subject area (expressed here as HESA cost code). The volatility is higher at smaller providers, as you might expect – while research in the arts and humanities is more likely to be funded by research councils than in STEM or social sciences. But it is really the volume, rather than the source, of research funding that determines how researcher salaries are paid.

    Although the established pathway from research postgraduate to research is by no means the only one available (many postgraduate research students do not become academics) it is an established maxim – dating back to the post-war Percy and Barlow reviews – that to produce the researchers we need requires training in the form of postgraduate research provision.

    Although it’s not really the purpose of this article, it is worth considering the subject and provider level distribution of postgraduate research students in the light of how funding and capacity for research is distributed. As the early research career is often dominated by the need to move to take on a fixed term contract, one way to address this might be to have research career opportunities and research students in the same place from the start.

    [Full screen]

    What can we learn from this?

    Research capacity, and – for that matter – research training capacity, can’t be turned off and on at a whim. Departments and research centres need more than one short-term funded project to begin delivering for the UK at their full potential, because developing capacity and expertise takes time and experience. That’s a part of the reason why we have non-ringfenced funding: streams like those associated with QR in England – to keep research viable between projects, and to nurture developing expertise so it can contribute meaningfully to national, regional, and industrial research priorities. It’s funds like these that support researcher training and supervision, and the infrastructure and support staff and components that make research possible.

    But what the data suggests is that while the short-term nature of project funding does have an impact, especially at smaller providers and emerging research centres, there are many universities that are able to sustain research employment between projects. A part of this is bound to be sheer scale, but it doesn’t happen at all large research performing organisations by any stretch of the imagination. A part of the answer then, must be the strategic decisions and staffing priorities that makes sustaining researcher employment possible.

    That’s not to let the funding side of the equation off the hook either. There is a sense that the Labour party was moving in the right direction in considering longer term research funding settlements – but we have yet to learn how this will work in practice. By its very nature, research is discovery and opportunity led: a few years ago artificial intelligence research was a minor academic curiosity, currently it is big money – but will it be a priority in 2035? Could there be some areas – medical and healthcare research, large scale physics, engineering – where we can be more sure than others?

    You’ll note we didn’t mention the arts, humanities, and social sciences in that list – but these may be some of the most valuable areas of human activity, and government-supported research plays a more prominent role in sustaining not just discovery and innovation but the actual practice of such activity. Such is the paucity of money available in the arts that many practitioners subsidise their practice with research and teaching – and it feels like arts funding more generally needs consideration.

    Sure, the UK punches above its weight in the sciences and in health care – but in arts, heritage, and social policy the work of the UK is genuinely world leading. It has a significant economic impact (second only to financial services) too. Research funding is a part of the picture here, but a long term commitment to these industries would be one of the most valuable decisions a government can make.

    What are the other choices?

    The fundamental challenge is maintaining a system which is dynamic, where the dynamism is not solely reliant on a highly transient workforce. A simple, albeit extremely limited, conclusion from the data would be that there is too great a supply of researchers to meet the demand for their skills.

    The more important question is what is the value of such a highly educated workforce and how can society make the most of their talents. This is not to say the UK should operate a supply led model. A world where funding is allocated based purely on the academic interests of researchers might be good for placing emphasis on intellectual curiosity but it would not allow funders to match social and economic priorities with researcher’s work. Put another way, it isn’t sufficient to tackle climate change by hoping enough researchers are interested in doing so. It would also not necessarily create more permanent jobs – just different ones.

    Conversely, a system which is largely demand led loses talent in other ways. The sheer exhaustion of moving between jobs and tacking research skills to different projects in the same field means stamina, not just research ability, is a key criterion for success. This means researchers whose abilities are needed are not deployed because their personal incentive for a more stable life trumps their career aspirations.

    The current system does penalise those who cannot work flexibly for extended periods of time, but more fundamentally the incentives in the system are misaligned to what it hopes to achieve. There can be no dynamism without some flexibility, but flexibility should be demonstrable not permanently designed. Flexibility of employment should be used to achieve a research benefit not only an administrative one.

    This is not wholly in the gift of universities. A careful consideration by government, funders, institutions, and researchers, of how flexibility should be used is the key to balance in the system. There are times where the research system requires stability. For example, the repeated use of fixed term contracts on the same topic is a clear market signal for more stable employment. Furthermore, it is undesirable to have a forever changing workforce in areas governments have singularly failed to make progress on for decades. Nobody is arguing that if only research into productivity was a bit more transient the UK’s economies woes could be fixed.

    The need is coordinated action. And unlike in Australia there is no single review of what the research ecosystem is for. Until then as priorities change, funders work on short time horizons, and institutions respond to ever changing incentives, the downstream effect is a workforce that will be treated as entirely changeable too.

    Source link

  • Research supervision in the context of REF – time for a step change?

    Research supervision in the context of REF – time for a step change?

    At a time when resources within research organisations are stretched, the PGR experience, and the role doctoral supervisors play in supporting that experience, needs closer attention.

    The release of the pilot indicators for the REF People Culture and Environment (PCE) has promoted a flurry of conversations across UK universities as to what ‘counts’. For the first time, institutions may evidence that “infrastructure, processes and mechanisms in place to support the training and supervision of research students are working effectively” and are invited to consider the inclusion of “pre and post training assessments” for supervisors.

    This signals to institutions that research supervision needs to be taken seriously– both in terms of quality and consistency of PGR experience, as well as the support and recognition for supervisors themselves. In doing so it validates the contribution of doctoral research to the research ecosystem.

    Accelerated prioritisation of research supervision shouldn’t come as a complete surprise. This lack of consistency in PGR experience was recognised less than a year ago in the UKRI New Deal for Postgraduate Research, which stated that “All PGR students should have access to high quality supervision and Research Organisations should ensure that everyone in the supervisory team is well supported, including through induction for new supervisors and Continuous Professional Development (CPD)”. That messaging has been repeated in the UKRI Revised Statement of Expectations for Doctoral Training (2024), alongside a call to research organisations to “build supervisor awareness of PGR mental health, wellbeing, bullying and harassment, and equality, diversity and inclusion issues.”

    So, what do we know about research supervision?

    Data from the UK Research Supervision Survey 2024 (UKRSS) confirms that, overwhelmingly, research supervision is considered valuable, rewarding and enjoyable by those who undertake it. Supervision also positively impacts upon their own research. However, a third of respondents reported feeling anxious about supervision and reported their main challenge was fostering student confidence and focus, followed by offering compassionate support to students facing difficult issues ranging from mental health and wellbeing, to finances and funding.

    Lack of time continues to be a barrier to high quality supervision practice, and rising supervisor-to-candidate ratios complicate this further. While early career supervisors were likely to be allocated one to two candidates, those later in their career could be supervising five to ten– only 30 per cent of UKRSS respondents reported that their institution had a policy on maximum candidate numbers. Respondents also made it clear that doctoral research supervision is not being adequately calculated into workload allocations, with a typically described workload model allocating 42 hours per candidate, per year, but supervisors reporting investing an average of 62 hours.

    Time constraints like these contribute greatly to the ability of supervisors to participate in CPD opportunities. This itself is a barrier to good supervision practice, as the UKRSS revealed that supervisors who engage in regular, mandatory CPD reported higher levels of confidence in all areas of supervisory practice. A staggering 91 per cent of respondents who had experienced mandatory induction reported they felt able to enact their institutions’ procedures around supervision– compared to 66 per cent of those for whom induction was not mandatory and 55 per cent who reported no mandatory requirements..

    The data illustrates that supervisors care about and take satisfaction from supporting the next generation of researchers, but they are getting a raw deal from their institutions in terms of time, reward, recognition and opportunities to develop and enhance their own practice. Underscoring this point, just 56 per cent of supervisors reported feeling valued by their institution, compared to 90 per cent who felt valued by their students. Until now this has gone under the radar, making the inclusion of the PCE indicators a welcome sign for those of us working to make changes within the sector.

    Engaging supervisors with high quality Continuing Professional Development

    Focus groups conducted with supervisors at five UK universities as part of the Research England funded Next Generation Research SuperVision Project (RSVP), have provided insight into what CPD is considered useful, meaningful and relevant. Supervisors were well aware of the need to develop and improve their practice, with one participant reflecting “… there isn’t sufficient training for supervision, you have a huge responsibility to another person’s career. So I think the idea that we ‘wing it’ perhaps shouldn’t be acceptable.”

    An overwhelming majority of participants reported that the most important aspects of their supervision practice and development come from interactions with, and support from, their peers and more experienced colleagues. The idea that supervision practice is best developed by watching other supervisors on the job and through communities of practice was repeated by participants across experience levels, genders, disciplines, and institutions– with some even claiming this to be the only way to become a truly good supervisor.

    Far from being reluctant to engage in professional development, many supervisors welcomed the idea of having the space and time to reflect on their practice. What they were less keen on was anything perceived as a ‘tick-box’ exercise– examples given included short courses without time for discussion, and self-directed online modules. There was a recognition by some that these approaches can be useful, but should form part of a more varied approach to CPD.

    Generally speaking, supervisors with less experience were more likely to engage in facilitated workshops and other interventions that help them understand their role and the doctoral journey. Those with more experience expressed a strong preference for discussion-based CPD, including peer reading groups, opportunities for facilitated reflection and mentoring.

    Recognising supervision as part of research culture

    Whatever the final version of the PCE metrics look like, there is now a growing body of empirical evidence to suggest that a revision in the way we manage, reward and recognise research supervision is needed. When government enabled universities to introduce fees for undergraduates the issue of quality assurance quickly surfaced. It was recognised that students should be taught by properly trained staff with a knowledge and understanding of pedagogy and approaches to learning and teaching. Arguably that moment has now come for research supervision.

    If the UK HE sector wishes to attract capable, committed, creative doctoral candidates from a range of backgrounds then those supervising them need to be treated, and trained, as professional practitioners. This means creating the time and space to enable supervisors at all levels of experience to engage in meaningful exchanges about their practice and to refresh their knowledge of policies and new areas as they arise.

    Quick wins?

    For institutions looking for ways to bolster their supervision support there are some empirically grounded ways to improve practice

    Firstly, tap into existing levers for change. The Concordat to Support the Career Development of Researchers outlines the need for PIs (many of whom are supervisors) to engage in professional development. Postdoctoral researchers are also required to engage in “10 days of professional development.” Since postdoctoral researchers are often informally involved in doctoral supervision (15% of the UKRSS respondents identified themselves as ‘early career researchers’) their engagement in CPD could also be counted. Actively recognising and celebrating the diversity of doctoral researchers and their supervisors also aligns with Athena Swan.

    Secondly, increase the visibility of provision. Many supervisors in the UKRSS and focus groups didn’t know what CPD was available in their institution. Very few knew about routes to recognition of supervisory practice (e.g.through the UKCGE Research Supervision Recognition Programme). There is little to be lost in an institution showcasing themselves to prospective researchers and funders as one which takes the quality of supervision seriously and actively invests, rewards and recognises supervisors.

    Thirdly, actively enable conversations about supervision. Aside from the formal training it is the time spent together which is often valuable. This may include offering simple opportunities for new and experienced supervisors to come together to talk about their experiences on topics that matter to them. It may mean enlisting a few champions who will speak about their experience. If there is already a mentoring scheme research supervision could be added to the list of topics that can be discussed as part of that relationship. It is also helpful to encourage supervisors to engage with the UKCGE Supervisor’s Network which offers cross-disciplinary and national level value as a community of practice.

    Finally, use existing PGR and supervisor networks and expert spaces to find out what works well and where the gaps are. Including working with RSVP which is designing, with 58 partners, CPD interventions for new and more experienced supervisors around the topics identified above. Following pilots and evaluation these will be made freely available to the sector. Specific resources to support supervisors to engender a *neurodiversity-affirmative culture will be available later this year. Webpages to support mentoring will be available very soon. Join the RSVP mailing list to be kept up to date.

     

    *with thanks to Professor Debi Riby at the centre for Neurodiversity & Development at Durham University

    Source link

  • You may not know this example of translation research, but it will have changed your life . . .

    You may not know this example of translation research, but it will have changed your life . . .

    Arguably, the most recognisable example of translational research in recent years was the swift development and rollout of the COVID-19 mRNA vaccine. The world was waiting for this research to meet its real-world ambition. Many members of the public would recognise that some of this research was undertaken at Oxford University and, with some exceptions, would also recognise the beneficial impact of the vaccine for both individuals and society. Following the rollout, there was even a public discussion that touched upon the idea of interdisciplinarity. How could the benefits of the COVID-19 vaccine be communicated to communities who felt reluctant to have the jab or distrustful of medical science?

    However, there was another piece of research that was translated into real-world effect with serendipitous timing.

    In 2013, Professor Andrew Ellis was working at the Aston Institute of Photonic Technologies. Ellis had previously worked at BT, where his observations and experience suggested that the ‘capacity’ needed in the telephone infrastructure had and would increase consistently over time and was consistently underestimated. Ellis recalls an ongoing refrain of ‘surely we have enough capacity already’. This continued to be true once the copper phone lines were used to deliver data for home internet usage.

    At this point, most residential properties were on ADSL (Asymmetric Digital Subscriber Line) internet connections. That is where copper wires are used to deliver broadband internet. Homes were typically working at speeds of around 8 megabits per second (Mbps).

    The Government had developed a strategy setting out that the majority of residential properties should be able to work at speeds of ‘at least 2 Mbps per second and 95% of the UK receiving far greater speeds (at least 24 Mbps) by 2017’. Fibre broadband was beginning to be rolled out, which used fibre optic cables to transmit data much more quickly. However, these fibre optic cables were generally only used to reach the street cabinet, with copper wires connecting the street cabinets to individual homes, restricting the broadband speed that could be achieved.

    From his previous work, Ellis could see that this ambition was neither competitive internationally nor of sufficient use long-term when demand for emerging applications was taken into account. He demonstrated that capacity was falling well below the predicted need and that the UK was slipping down the league table for connectivity in economically developed countries. Estonia, Poland, Korea and Norway were all streaking ahead.

    Ellis contacted MPs working on this strategy via the Industry and Parliament Trust. Two breakfast meetings and a dinner meeting were held to discuss the lack of ambition in the strategy. However, only the fortuitous attendance of a senior civil servant at the dinner meeting led to a policy breakthrough. Further momentum and publicity were generated by a meeting organised by the Royal Society to discuss ‘Communication networks beyond the capacity crunch’, including a presentation by Dr Andrew Lord.

    Ellis was lobbying for an increase in ambition. There was resistance to this as there was no additional money to spend on improving infrastructure outside of the spending review cycle. Ellis convinced the Government that no additional spending was needed to change the ambition. Changing a number in a policy document wouldn’t (on this occasion) cost the government any more money. (The terms ‘pure-fibre’ and ‘full-fibre’ were also coined at these meetings, meaning using fibre optics cables to the street cabinet and from the cabinet to individual homes.)

    With the Government changing their ambition, providers such as Clear Fibre, Gigaclear and BT Openreach would need to improve the infrastructure to deliver faster broadband to our homes.

    It was estimated that upgrading the whole UK to full fibre would cost £40-60 billion as part of the EU-funded Discus project. Research by the AiPT team showed that it would be closer to £8-10 billion if the network was reconfigured according to their research proposals, a one-for-one replacement of network equipment from copper to fibre-based ones. Further, research demonstrated that fibre is also more energy efficient.

    Optical networks were using about 2% of the electricity in the developing world. (Ellis explained that BT objected to this figure, stating that it was, in fact, 1.96%!) Not only was a full-fibre network faster, it was also more energy efficient. (This now pales in significance to the energy consumption that will increasingly be needed to power AI data centres.)

    BT began rolling out full-fibre broadband to 80% of the UK. In 2019, BT hired heavily for this work, much of which was completed in the first few months of 2020. The increased activity and presence of BT vans helped fuel the 5G coronavirus conspiracy!

    In a moment of serendipity, this meant that by the 23rd of March 2020, when the then Prime Minister, Boris Johnson, announced the first lockdown, there was enough access capacity for many of us to begin working at home. As we got used to Zoom and Teams, multiple people were using video calls in one household for work and homeschooling. Not only did this allow for a relatively smooth transition to remote working, but it allowed our children to continue accessing their education and for us to keep in touch with friends and family (Zoom quiz, anyone?) The societal shift to remote working, prompted by lockdowns but enabled by full-fibre, remains both contested in terms of productivity and profound in terms of impact.

    I asked Andrew what challenges he faced when trying to inform industry and policy of his research. He noted three key barriers:

    1. To impact Government policy, one needs to know the right person to talk to. There must be barriers to prevent a free-for-all lobbying system of civil servants. However, policy institutes, research impact centres and organisations such as the IPT should be able to facilitate connections when this is helpful to both parties.
    2. The second – is the structure of academic contracts. New ideas often come from, and are certainly implemented by, PhD students and Research Assistants. However, given that most research assistants are on two- or three-year contracts, their eyes are firmly on improving their CV to land the next contract. This often leads them to focus almost entirely on publications. To build good links with industry and engage in long-term strategy, longer-term job contracts are needed.
    3. Similarly, he feels a strong tension between metrics, such as 4* papers, required for REF and rapid publication of results in outlets read or attended by decision-makers in industry, where solutions are often required in months rather than years

    Whilst the success of the COVID vaccine development may have made global headlines, the work of the AiPT’s team (Andrew believes that others lobbied on the same topic, including Professor Dimitra Simeonidou at the University of Bristol, Professor Polina Bayvel CBE at University College London and Professor Sir David Payne at Southampton University) quietly allowed many of us to continue working and to be connected to our colleagues, friends, and family throughout the pandemic. Further, as Professor Sarah Gilbert, Professor of Vaccinology at the Jenner Institute and lead scientist on the vaccine project, explains, the ability to work remotely with trial volunteers (giving them information via video instead of in-person presentations) and collaborating with colleagues across the globe was vital in the vaccine production itself.

    Source link