Industrial strategy for post-Covid Britain: a renewed public purpose for the state and business
Bibliographic record
Abstract
There is no doubt that the UK economy will take a big hit from the Covid-19 pandemic. Estimates of its actual impact vary, but, at the time of writing, most commentators put the figure at between 11 and 14.5 per cent. To put that into perspective, following the 2007–09 financial crisis, between the first quarter of 2008 and the second quarter of 2009 the UK economy shrank by a little over 6 per cent, and it then took five years to regain its pre-crisis size. The sheer scale of the Covid-19 impact means that the state's support for the recovery will need to include an industrial strategy – something that Britain has not seen in over 40 years. The nature and effectiveness of that strategy will largely depend upon the relationships between government and the various industrial sectors; much will also hinge on the question “What are companies actually for?”. From Margaret Thatcher's election in May 1979 until very recently, the answer was a very definite “Making profits and delivering value to shareholders”. But fallout from recent events, reminiscent of the interwar years, proves that it is just not that simple. Beyond profit: the question of corporate purpose Part of the United Kingdom's response to the 2007–09 financial crisis was to bail out financial institutions deemed “too big to fail”. The fear was that, had they not been rescued, the resulting damage would be more than purely economic. The social dislocation resulting from account holders having no access to funds, losing their savings or being unable to pay their mortgages – plus the consequences of increased unemployment caused by the “Great Recession” that followed – would have been enormous. The bailouts were therefore a de facto admission that businesses are indeed about more than profit. If that message needed any more reinforcement, it came in the form of admissions, by every government since 2008, that the economy needed rebalancing, with a new emphasis on manufacturing. We have yet to see any action, though. As it stands, the government's proposed post-pandemic recovery programme offers a lot of infrastructure investment; but, inexplicably, both industrial strategy and a business bank remain absent.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".