SHAPE Shifters
ARC Accelerator Co-founder and Director Chris Fellingham on the commercialisation potential of social sciences, arts and humanities
If you suggest to a venture capitalist (VC) the idea of scouting social science university departments for potential founders, they will raise an eyebrow and likely won’t take you seriously again. They wouldn’t be wrong.
VCs are gold miners. To be VC-backable, a venture should have billion-dollar potential and be among the top 1% of opportunities to justify the high-risk, high-return investing model. However smart, interesting, scalable, or profitable the idea might be, if it doesn’t have sector-redefining, world-altering potential, VCs are not interested.
At the same time, we have social scientists – a group whose minds are wired to identify, study and test solutions to societal problems – at a national and indeed global level. Isn’t this a foundation for transformative change? Social scientists have deep insights and answers to many pressing issues. If that can’t be translated into solutions, something must be broken or underbuilt.
I asked Chris Fellingham, Co-Founder and Director of ARC Accelerator, for his take on this. ARC is a first-of-its-kind incubator and accelerator supporting academics from SHAPE (Social sciences, Humanities and Arts for People and the Economy) fields in turning ideas based on their research into impactful ventures.
What we discussed
How ARC Accelerator came about and what gaps in research commercialisation landscape it fills
Challenges of telling the impact story of SHAPE-based ventures
The differences between STEM and SHAPE commercialisation
SHAPE-based company archetypes, business models, and success stories
Commercialisation potential of pure versus computational social science and digital humanities
What it would take for SHAPE ventures to become VC-backable, and what high-risk high-reward work looks like in this space
How we can get more SHAPE commercialisation, and with greater impact
Lessons for maximising the impact of social sciences, arts and humanities
For founders:
Value what you offer: be comfortable with charging for your time, advice, and services
Raise ambition: leave academic caution and tentativeness in the lab, don’t bring it to the market – and aim to tackle bigger problems
Hire and delegate: focus on areas where you can add the most value and hire for other roles
For the Government, research funders, and universities
Change the impact appetite of research funders: research funders need to have an understanding of what the impact of SHAPE research looks like. The ‘outputs’ section of funding calls should go beyond publications more often to incentivise research with high impact potential
Fund the ‘last mile’: fund not just research but also its pathway from the lab into public use. This is especially important for applied research intended to have real-world impact
Educate TTOs: ensure technology transfer offices are well-versed in social science, humanities and arts to support the commercialisation of research in these disciplines
Bridge the gap between applied research and intended beneficiaries: utilise intermediary institutions, such as the Education Endowment fund, that help support translational and pilot funding for research
Escape a grey zone: review the UKRI funding terms and conditions to ensure they don’t affect the eligibility of PhD students to participate in research commercialisation programmes
Expand training for PhD and early-career researchers: help them to build transferable skills enabling those who don’t pursue an academic career to take their expertise into other organisations or launch a startup
Explore alternative market funding mechanisms for interventions: carbon pricing has helped develop the climate tech market. Equivalent thresholds or advanced market commitments in QALYs or educational attainment could help bring innovations into these areas
Full interview
How has the ARC Accelerator come about? What has led you to focus on SHAPE (Social sciences, Humanities and Arts for People and the Economy) disciplines?
ARC was founded in 2020 as part of the ASPECT network, a group of then six universities (now 45+) that collectively recognised there wasn’t much happening in social science commercialisation. So, they put in a bid to Research England to explore and promote it.
After winning the bid, the technology transfer group within ASPECT, which I was part of, discussed how to best use the funding. Initially, we considered creating a pilot fund for social science projects to see if we could get a few launched as a proof of concept. But Tony Walker, who was at the University of Manchester technology transfer office (TTO) at the time, suggested creating an ICURe-like commercialisation programme specifically for social science.
We knew that ICURe, while excellent for physical and life sciences, wasn’t well-suited for social sciences. It was, rightly, product and patent-focused, with an endpoint of pitching to VCs. Social science researchers often felt uncomfortable with this model, as their commercialisation pathways seemed different from STEM pathways. For example, when asked about their IP defence strategy or what they could patent, social scientists would often respond with “probably nothing.” This led to doubts, “If I can’t patent, should I even commercialise?”
Based on this, we decided to create a pilot programme, which became ARC. We ran it for three years under Research England funding. During that time, we were in conversation with the Economic and Social Research Council (ESRC) and the Arts and Humanities Research Council (AHRC), who had been looking at commercialisation more broadly and had done a pilot with the Healthy Ageing Catalyst. While it was great, it only covered a specific slice. What was missing in the UK landscape was a general-purpose accelerator for all social sciences, humanities, and arts. This led to a bid for an accelerator, which we won, and that became what we have now – the ESRC/AHRC SHAPE Catalyst, also known as the ARC Accelerator.
Did you see much interest from potential participants at the start? Have you noticed any changes in demand over time?
Yes, there were quite a lot of applications at the start. I think that was due to pent-up demand. It was clear that by creating a space specifically for SHAPE researchers, they felt confident enough to come forward. There’s a lot of value in creating something and telling a specific group that hasn’t been explicitly served before that “this is for you.” We had researchers that TTOs didn’t know were interested in coming forward.
But we faced two challenges. After the second year, the pent-up demand started slacking off a little, especially from institutions that had initially provided many applicants. We maintained good numbers, but new applicants were predominantly from new institutions joining the ASPECT network. We also realised that many people weren’t quite ready for a full accelerator programme. For example, some were still considering ethical issues about commercialisation.
To address these challenges, Julian Jantke (then at University of Bristol and now my Co-Founder at Kindling) saw that we needed earlier stage programmes that were more light-touch, giving SHAPE researchers a space to explore commercial potential without having to commit to a full accelerator. We called these Discover and Launch. Both are online and run all year. Discover introduces core concepts and tools for researchers, it’s more “just find out.” Launch is four to five sessions over two months that let researchers dip their toes in the water of commercialisation. They look at business models and do some light-touch validation. If researchers are still keen on commercialisation after Discover and Launch, then we can be more confident they’ve thought about the process deeply, have a sense of what’s involved and are better prepared for Accelerate, which demands much more time and commitment.
Put together, these form a guided pathway as well as an early-stage pipeline which each successive stage can build on. We have about 400 people a year in Discover, which is critical due to how new commercialisation is in social sciences, humanities, and arts. This high-volume approach is necessary for culture change and awareness, as well as building a pipeline for later-stage projects. From those 400, about 120 people make it to Launch, and then 20 make it to Accelerate.
Is there a common participant profile at ARC? Is it mostly postgraduate students, early-career scholars, or people further along in the academic system?
The profile of participants is quite spread out. The age distribution skews slightly older. I’d say the mode age is people in their forties and early-fifties. This is likely because these researchers have mature projects in research terms and may have developed sophisticated ideas about what impact might look like.
But younger researchers are starting to look at commercialisation. I think this is partly due to a generational shift in entrepreneurial culture among researchers, which is beginning to feed through. For example, when I was an undergraduate, entrepreneurship wasn’t a big focus. But ten years later, most universities had numerous entrepreneurial offerings for both undergraduates and postgraduates, the cultural attitude towards entrepreneurship has changed, and that generation is now beginning their research careers, which is exciting.
Another interesting point is that the majority are female founders, which is different from STEM commercialisation which at least historically has skewed male. I’m not quite sure why that is – it could simply match the base demographics in SHAPE fields, or there might be something else at play.
TTOs are a significant vehicle for research commercialisation. How does ARC work alongside them?
We work pretty closely with TTOs and we consider that a strength of the programme. TTOs can help participants navigate university processes, get payments for work, as well as bringing their own networks, advice and support, which is crucial. Accelerators are hard work and having someone advocating, to bounce ideas off and support you, is critical.
TTOs are also important for the commercialisation journey itself. Say an academic wants to run a pilot workshop – they may wish to use university consultancy services to do so (typically run via TTOs) and will want things like insurance and lawyers to manage those transactions.
We also help TTOs upskill, especially in SHAPE commercialisation. Going through ARC is an efficient way for them to build knowledge and skills in this space quickly. Even active institutions like Cambridge might only deal with a handful of such projects per year which can be a slow rate of learning. Through ARC, they can see 20-30 projects within six months, significantly broadening their awareness. TTOs also get to meet and collaborate with other TTOs, which is rare outside their own office. This allows for sharing contacts, approaches, and best practices.
Are there many initiatives doing anything similar? How common are SHAPE-focused incubators or accelerators like ARC? How does the UK compare on this front to other countries?
I’m fairly confident the answer is no. We talk a lot with universities in the US, Canada, Australia, Europe, East Asia, South Africa, and I haven’t come across a SHAPE accelerator. That’s a matter of time though. Universities in those regions are very interested. I suspect we’ll see them emerging in the next 18 months.
The closest you typically get are social venture accelerators. Given over half of SHAPE ventures tend to be social ventures, a social venture accelerator will very likely have these kinds of projects in them, and much of the commercialisation journey is comparable.
The startup and progress community often believes that the UK is not reaching its full potential in innovation and research. However, there is a growing willingness to take bold steps. The SHAPE space is a good case in point. While some SHAPE spinouts have emerged from universities overseas, such as Good Judgment from the University of Pennsylvania, there hasn’t been a systematic approach to fostering these ventures as there has been with STEM fields. The UK has demonstrated genuine leadership in this area.
The UK’s adoption of the Research Excellence Framework (REF), while not being perfect, does drive impact. If you build a venture based on your research, that’s a very powerful impact case study which is critical for universities and departments in terms of reputation and income.
We’ve already touched on ARC’s founding story and how you secured funding. But I imagine that was not the only avenue you explored. What was your experience with pitching ARC to external funders and other kinds of potential supporters? How did you find the process of convincing people about the commercialisation potential of SHAPE research and growth of such companies?
The research councils, particularly ESRC and AHRC, have been fantastic. I think they always had a sense that SHAPE would need its own support structures within the research landscape. They were keen to demonstrate to the rest of the research community that SHAPE could do some really good stuff if supported correctly.
Pitching outside of that community, such as external funders, mentors, or partners, has been much harder. No one really understands what a SHAPE venture is. The core concept often goes over everyone’s head, which is understandable, as it’s new. Initially, we struggled with people questioning whether SHAPE needed anything different, or why can’t it use existing commercialisation structures and programmes. It’s taken us a while to explain that the pathway for SHAPE is very different. Such ventures might not go to VC, they might do service-based businesses before product-based businesses, and they’re targeting different sectors. All of this necessitates a separate programme.
I’m not sure those outside of universities will ever think of SHAPE ventures. We’ll probably need to talk about it on a sectoral basis, like EdTech or climate, or on a business model basis, like consultancy-based businesses or social enterprises. People understand these terms, and they represent somewhat independent ecosystems. For example, if I’m pitching an EdTech venture, I can speak to an EdTech investor or angel, and they’ll understand. But there’s no ‘SHAPE angel’ or ‘SHAPE investor’. So we’ll likely need to use this more familiar language when talking to external stakeholders.
What does commercialised SHAPE research look like? What are some company archetypes that you see most often at ARC and in the non-STEM space more broadly? How do business models, goals, and challenges compare to VC-backable companies?
These ventures are often not primarily profit-driven. They prioritise social impact over rapid growth and high returns. This approach presents challenges, compared to traditional VC-backable companies. SHAPE ventures are generally less scalable, except for software-based ones, often target the public sector areas, such as health, social care, environment, education, and criminal justice, which can be slower to adopt innovations, and may not align with traditional VC expectations for growth and returns. This orientation can make them less attractive to VC funding but more suited to impact investing or public sector funding.
Commercialised SHAPE research typically takes the form of service-based companies at the start, with about 80% falling into this category. Approximately 60-70% are social ventures which might not want to make any profit. If they do, they would recycle it straight back into the venture, and a percentage of those might become Community Interest Companies or charities.
The consultancy model is very typical. An academic might say, “I’m an expert in this field with real insight into solving this problem based on years of research. Now I’m going to help organisations solve it.” A good example is Equal In-Sight, founded by Roberta Guerrina at Bristol. She saw that many companies wanted to create diverse and inclusive environments and had policies in place. But there were questions: Which policies actually work? What constitutes good implementation? This was the focus of her research through which she engaged with numerous organisations. Eventually, some of them approached her saying, “You’ve worked with us on the research side; why don’t you help us implement this on a consultancy basis?” From there, she began offering consultancy services through the university. Over time, she started productising her advice and approaches which led to a full-fledged consultancy business.
Other common company archetypes are train-the-trainer, which offers non-digital scalability, and certification or accreditation services for organisations in areas like ESG or carbon reduction, leveraging academic reputation as a quality mark.
Around 5-10% are software-based. An example of this is the Teacher Success Platform developed by Rob Klassen, who was at the University of York at the time, which is a digital tool for selecting better teachers and improving their performance. His definition of better centred on one metric: their capacity to manage classroom disruptions. He viewed disruptions as lost learning minutes, which over an academic year could lead to poorer educational outcomes. To address this, he designed a digital tool that scenario-tested prospective teachers, identifying those who could select better interventions and reduce total disruption time. He then developed a tool to improve this skill. Now, over 150,000 educators are using it across North America, Europe, MENA, and other regions. Additional services can be wrapped around it too, so this type of venture has the scalability inherent to software products.
You mentioned software-based SHAPE ventures. In terms of academic disciplines, on the one hand, we have pure social sciences, arts and humanities. On the other, we have computational social sciences and digital humanities that have people with skills related to computer science and software engineering. They are writing state-of-the-art software for their research. What does this mean for the commercialisation potential?
If you consider pure financial upside, there’s no doubt that software has a higher ceiling than any of the other options. But it doesn’t necessarily mean it’s more likely to succeed. Someone could create a great piece of software that has absolutely no customer viability. However, other things being equal, having a software component definitely helps. If we look at our most successful ventures, most of them have at least some digital component to them. I only expect this trend to increase in the future.
SHAPE researchers often develop deep expertise with certain types of data that can be immensely valuable. I saw this when I worked at FutureLearn. How do you design, measure and create learning interventions that work at a scale of tens of thousands of users? Data scientists alone can only go so far. From economics to education and genealogical data in churches (a real spinout that was acquired), I think there is huge potential.
There is a common belief that SHAPE-focused companies are not VC-backable. At the same time, we’re seeing the Advanced Research and Innovation Agency (ARIA), which operates in a VC-backable space, being open to funding SHAPE proposals as part of their programmes (for example, the Climate Cooling programme). What does it take for SHAPE-based work to become VC-backable? Do you see that often?
When we think about what makes a venture VC-backable, it typically needs to be scalable, in a sufficiently large market for the VC to get their return, have a strong team, and a compelling product. Most SHAPE ventures, at least initially, don’t meet these criteria.
Of these, one of the hardest to overcome is market size. Many SHAPE ventures target areas in the public sector like criminal justice, education, health and social care. These are shallow markets which are often entirely dependent on the public sector and are cash constrained. This makes it challenging for VCs to see potential for significant returns. They will say, “Well, there’s not much money in primary schools in the UK.” And they’re right.
However, not getting VC funding at the start doesn’t mean it won’t come later. We saw some ventures attracting VC interest after two or three years of commercialisation, when they’ve built up customers and developed their product, effectively de-risking the proposition for VCs.
While traditional VCs might be less interested, impact VCs and philanthropic investors could be very attracted to SHAPE ventures. These ventures often have a strong research basis, which makes them appealing to funders looking for evidence-based solutions to social problems. If a philanthropic investor wants to solve a problem like poverty and wants to know that the intervention works with a high degree of certainty, research-based approaches offer the highest level of credibility. You can point to randomised controlled trials, years of peer-reviewed research, refinement of methods, and pilots with reputable organisations like UNICEF. It’s essentially a deep social venture, which could be considered a separate asset class. This approach aligns well with the goals of philanthropic capital.
What does success look like for such companies?
Many SHAPE-based companies are already quite successful, or at least on a clear pathway to success. The problem is they don’t get enough recognition for their success.
Let me give you an example. There’s a company from Oxford called OxEd. They use a form of cognitive assessment to identify how well children aged between five and eight are doing in the classroom, based on their language fluency and ability to understand the teacher. They didn’t get VC money at the start, but the founders believed in their product and decided to spin out from Oxford anyway. Initially, we thought it would be tough for them as they were selling to primary schools, which are often underfunded. But then the pandemic hit, and suddenly the Department for Education (DfE) needed a way to identify which kids at home were falling behind. OxEd’s software-based tablet application could identify pupils at risk and provide interventions for those falling behind. They were able to win successive DfE contracts, have since worked with over half the primary schools in England and are now expanding internationally.
This is a story that wasn’t widely told. During the pandemic, the impact on children’s education was a significant issue. Social science research had answers to that and provided a pathway through.
We’ve had more success stories. One I really like is HistoryCity founded by historians from the University of Exeter. It’s a theme we see quite often: researchers thinking about how to support heritage and history. HistoryCity offers immersive trails in European cities for people who want a different way of interacting with urban environments. They’ve partnered with organisations like the National Trust and museums, layering onto existing offerings and increasing footfall to museums. It’s an app-based, software solution that combines history and heritage engagement.
Another example is One World Together founded by Niki Banks, Professor of International Development at Manchester. This is what I’d call a deep social venture. Banks focused on the issue of aid money not reaching communities effectively. She built a digital platform that enables more direct donations, reducing operational and administrative costs that many charities face. This also created a low entry point for non-traditional donors like students to start giving to charities. This venture innovated on both the donation and recipient sides and has been growing successfully.
So, I believe there needs to be more recognition of the powerful interventions that are possible through SHAPE ventures. Their impact is real, but it often goes unnoticed or underappreciated.
How can we get more SHAPE commercialisation, and with greater impact?
With a caveat that budgets are under exceptional pressure, it’s still fundamental that if we fund applied research that is designed to be impactful, we should enable it to make the ‘last mile’ from the lab into public use, and that should be included as part of the funding or through programmes like ARC. It doesn’t make sense to have great research published, only for nothing to then happen. Of course, not all research is a good fit for commercialisation, nor should it be.
Alongside funding impact pathways, I’d like to see more work go into interventions as into studying problems. Many researchers have a deep understanding of a particular problem but lack insight into what a good intervention for that problem would be. For example, in addressing homelessness, it’s not enough to understand all the causal factors – you wouldn’t leaflet houses to tell people how to avoid these causes. You do however need to know what interventions actually work, which don’t, and why, and how to test others. This might mean larger or interdisciplinary research teams or working even more with external organisations that can bring different skill sets and experiences to bear. I’d like to see more joined-up work combining excellent problem analysis with intervention expertise.
Overall though, raising awareness and providing spaces for SHAPE researchers to learn and explore impact pathways will lead to more and more impactful research.
What could this look like in practice? What role could the Government, or specifically research funders like UKRI play? For instance, ESRC funding calls often list publications as expected outputs. Could specifying other forms of output incentivise more ambition in terms of impact?
I’m not familiar with exactly how research grants, and specifically impact, are assessed and by who. However, SHAPE ventures are so new that I suspect it is a little known impact pathway and very unlikely to be widely understood.
But I think that awareness piece also applies to the research-side. How many researchers, when they’re writing their research grant, know what a social venture as research output would look like, or have any training to do that? I think that’s a big part of it.
That is beginning to change. We’ve already had researchers tell us they rewrote grant applications, with ventures in mind, once they went on our programme.
There are also some fantastic intermediary organisations that help bridge the gap between research and impact. The Education Endowment fund, for example, supports research which can include software prototypes for randomised controlled trials and commercialisation. That is because they have a clear end goal: “How do we improve educational attainment in the classroom?” More organisations or mechanisms like that would help unlock the potential of SHAPE research.
You mentioned awareness among researchers. Does this mean that we need to reimagine the design of PhD programmes? Developing that awareness and problem-solution mindset probably starts right there, or perhaps even earlier, at the Master’s or undergraduate level. What do you think the role of curriculum design can play here?
I completely agree, and that’s a low-hanging fruit. The ICURe programme has a good diagram which they show at the start of every cohort. It’s quite brutal – it shows how many PhD students will eventually make it to tenure. The answer is something ludicrously small, around 0.2%. Their point is that most PhD students will never get tenure or have a long career in academia.
It’s a harsh message, but their point is: you’re super smart, you’re going to have amazing subject matter expertise. Maybe entrepreneurship is a really good way, even if you don’t end up being an entrepreneur, to learn important skills around your subject matter expertise. I think this approach could easily be more systematic across the post-PhD and early-career researcher landscape in the UK.
Probably the most financially successful academic spinout in this space was the climate change economic modelling consultancy Vivid Economics, which was acquired by McKinsey. There are a handful of similar examples from economics, but given the areas they focus on and the potential customers they could have, like financial institutions, we should be seeing a lot more of them. I think it’s because most academics aren’t aware that commercialisation is a viable option for them.
What does risk-taking look like in the context of SHAPE ventures? Take the social sciences – there are methodological challenges, such as ethics and unintended consequences of randomised controlled trials, or ethnography in conflict zones. But these seem to lean more towards research methodology rather than company-building. I get a sense that we don’t really know what high-risk, high-reward work in the case of SHAPE could look like. What’s your take on this?
I think ethics is definitely a big risk area, and it’s one that SHAPE researchers take very seriously. STEM researchers also take it seriously, but SHAPE researchers might be more concerned about commercialisation and risk than STEM researchers are. I suspect it’s because commercialisation is just a newer concept for them.
I was reading Troublemakers by Leslie Berlin and was struck by the extent to which Stanley Cohen, working on recombinant DNA in the 1970s, was wrestling with the ethics of commercialising his research. At the time, this researcher was extremely worried about what their peers in the research field would think of them for pursuing commercialisation. It was a massive preoccupation. This isn’t nearly as controversial now within medical science as it was when that research was being done. Obviously, it’s because that researcher was one of the first to do it. I think there’s some of that with SHAPE. Since so few people know peers who have done it, it carries a higher kind of ethical and social risk.
In terms of the research itself, I’m not sure. The high-risk, high-reward in STEM is, “We’re going to go after this really bold vision, and it’s got a super high chance of failure. But if it comes off, we get some form of quantum computing” I wonder if there’s an epistemological reason why that wouldn’t quite be the same in SHAPE. Maybe the curve on the risk-reward looks different because the underlying data is contextual in a way that hard science data is not.
I also wonder if it’s harder to get a high reward as opposed to incremental reward in SHAPE. Most of SHAPE still focuses on humans, and it’s not obvious to me that humans can easily experience a step change. But if you get, say, a 0.5% improvement in mathematical attainment between ages nine and eleven, that’s actually a really big deal, even though it’s incremental.
Perhaps researchers like Melissa Dell or Raj Chetty, who are doing computational big data work could have a high-risk, high-reward scenario. Their point of intervention might be at the government level, where they could say, “We can change how you understand inequality, and we can give you some very powerful macro-level economic tools to do so.” In this case, that would indeed be a high-risk, high-reward situation. The potential impact on policy and society could be significant if successful, but the challenges and risks involved in implementing such large-scale changes would also be considerable.
If you were advising the Department for Science, Innovation and Technology or Department for Education now, what would be your priority areas? What changes would you like to see?
I’d like to see more intermediary organisations and funding to help bridge fantastic ideas and interventions, launching pilots, prototypes and early-stage commercialisation.
My bolder idea would be more market-driven funding mechanisms that can support innovations in areas we know are economically beneficial but for which we don’t have markets. Think about public health or education. We have a pretty good understanding of the benefits and their economic value, yet many innovations can’t get off the ground, because there is no funding. I’d love to see mechanisms that say, “If you can improve maths attainment on this metric for this age group, we will fund it.” I find it difficult to accept that we can know something is critical economically and yet we don’t fund it, because the current market structures are too narrow to include it.
What is your advice to the founders who are trying to build a company in the SHAPE space?
Firstly, researchers need to value what they’re offering, including financially. The instinct is always to give it away for free, and I understand that. But what I always tell them is that their time is not free. So, recognising that it’s okay to value it and charge for it is important. Lots of people are selling services to various organisations, and those organisations are happy to pay for it. If researchers think their service is great, they should be comfortable charging for it. That would be my top advice, and we spend a lot of time with researchers helping them do that.
Secondly, raising ambition. I think a lot of them are tackling really big, hard problems, and they could always go bigger and raise their ambition. As researchers, they’re naturally cautious about saying anything that can’t be really evidenced and are very tentative about everything. But actually, I think they need to be a bit more confident and louder.
Lastly, where possible, hire and delegate, and think about where they want to add value. A lot of researchers never really want to be CEOs. I think they would rather be a Chief Technical Officer or a Chief Scientific Officer, and that’s okay. They should try to find someone who wants to do the other parts of the business that they don’t want to do. Doing so might be difficult, because it’s very hard to delegate something that you understand really well and care about. But doing so will unlock a lot more of their potential to develop the product or service. So, my advice is to delegate and hire where possible.
We ask all our guests the same closing question: what’s one interesting thing you’ve read or listened to recently that you’d like to share with our readers?
A Culture of Growth by Joel Mokyr is brilliant. It tries to understand why the Industrial Revolution took off in Western Europe at the time it did, and not in other countries that were arguably better placed. The nub of it explains how, somewhat fortuitously, an open intellectual culture, not a guarantee in those times, combined with a fusion of different types of knowledge from practitioners to theorists came together. Lessons to be drawn, but mostly just very good history.
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