The Government toughens up on school reopenings

3 Jul

Public compliance has been essential in the Government’s fight against Coronavirus, and although it has arguably been successful in imposing lockdown, getting life back to normal looks rather more challenging. Case in point: the enormous difficulties the Education Secretary has had in trying to reopen schools.

After months of confusion and resistance from parents, teachers, unions, the Labour Party, and seemingly everyone with an opinion, Gavin Williamson put his foot down earlier this week.

On LBC, he said that parents who would not send their children back to school in the upcoming academic year (beginning September) would be fined, unless they have a “good reason” or subject to a local spike. It’s the first time the Government has exerted real authority on the matter. 

Crucially, the Government substantially enhanced its guidance for how schools can reopen safely. Some of these steps include administering Covid-19 tests to all schools and colleges, creating “bubbles” between year groups so that they have different lunch and break times, and adapting classrooms, so that windows are open and tables are facing the same way.

Even so, one suspects that the unions still won’t be happy… One of the worst parts of the school saga is that it was completely hijacked by their noisy selves. At every step, they polarised the issue to deeply unhelpful levels, including telling teachers not to engage with planning officials, in doing so obscuring the voices of those who wanted to work through perfectly reasonable concerns.

One worry was simply about consistency in health advice. As one headteacher told ConservativeHome a few weeks ago: “it’s quite worrying when the Government guidance goes from ‘Stay at home, protect the NHS, save lives, do not go anywhere near anybody’ to then suddenly ‘actually you don’t really need to socially distance with little ones anyway, so it will be fine’. That doesn’t feel like a confidence-giving statement.”

Many felt that the guidance had not gone far enough – and lacked a realism about young children’s ability to socially distance.

Moreover, the headteacher said that the Department of Education had been poor in terms of educational resources, adding: “nowhere… does it say what schools should be doing to provide online provision for children who are not at school. So every school in the country has translated that differently and is offering something different, and it becomes a pure lottery.”

Such concerns – that the schools closures were highlighting inequalities in the educational system – became central to more recent debates on reopening schools. There’s a sense that the focus has shifted, with the societal consequences of staying off school (domestic violence, mental health, parents’ inability to work, and the rest) outweighing the direct health risk of Covid-19, hence why the Government has now offered a £1 billion Covid catch-up package – in addition to £14 billion being invested over the next three years.

Much of the Government’s insistence on schools going back is no doubt directed by health experts’ increasing belief that children do not transmit, or pass, Covid-19 to the same extent as adults; a phenomenon increasingly highlighted through the safe reopening of schools elsewhere in Europe.

But, as with all things Coronavirus-related, there are no certainties, so the Government cannot reassure teachers and educational staff in the way it would like. Ultimately it’s worth remembering, though, that it cannot legislate around every difficulty that this virus might bring, and at some point we are – not just schools – simply going to have to get on with things.

Labour, too, has to take responsibility for the difficulties in reopening schools. The party saw the issue as a political football from the start, allowing the unions to dominate the Left’s response. For all who hoped of some national solidarity during a pandemic, watching these unhelpful criticisms – especially given the socioeconomic damage leaving schools closed will cause – was deeply depressing.

Even now Kate Green, the Shadow Education Secretary, has laid into Williamson on fines, warning that they will affect poorer patients. But faced with some of the biggest resistance in the Covid-19 crisis – and an issue that’ll leave all children worse off for years, the Education Secretary simply had to get tough. “About time,” many will think.

John Bald: Williamson is right. Pupils should sit in rows facing the teacher.

1 Jul

John Bald is a former Ofsted inspector and has written two books on the history of writing and spelling. He is Vice President of the Conservative Education Society.

Gavin Williamson’s statement that school pupils should sit in rows facing the teacher and pay attention, was predictably denounced by progressives as ill-informed, authoritarian, and near-fascist. Unfortunately for those who think he should be accountable to Twitter rather than Parliament, his view is correct, and supported not only by the results of schools such as West London Free, Michaela, and the best academies, but by the most recent evidence on the way the brain forms the neural networks that embody learning. His point about coronavirus spreading more easily if children sit facing each other is important in current circumstances, but the evidence on concentration and learning is permanent, and validates the reforms to teaching and learning made by headteachers and Conservative ministers since the opening of Mossbourne in 2005.

The most important source is the recent book How We Learn, by Professor Stanislas Dehaene, director of cognitive neuroimaging at the French national health and scientific research institute INSERM. Dehaene demonstrates by experiment that, from babyhood, we form working views and hypotheses about the world, which we modify when we encounter something that does not fit them. This continues throughout life, and is consistent with much scientific activity as discussed in Thomas Kuhn’s The Structure of Scientific Revolutions. An example is Galileo’s discovery of the movement of Jupiter’s moons, which was inconsistent with the notion that the universe revolved round the earth. Dehaene sees the same process as the key to developing artificial intelligence, where computers are turned in on themselves to produce the same outcome, albeit less efficiently.

I’ve reviewed the book in detail here, and checked the review with the author. Salient points are his endorsement of phonics as the basis of teaching reading in French as well as English – to establish the alphabetic principle, which is then modified to take account of the respective variations in each language – and the effect of focus and concentration on the development of neural networks. We need, he says, to teach children to pay close attention to the teacher, not to restore the former “magisterial” style, where the teacher simply dictated and pupils copied, but to stimulate brain activity and hence learning. This is what the schools mentioned above set out to do, and the reason why their results have shot up. For the Secretary of State to recommend that others adopt this successful approach is not ideology, but common sense. The progressive “blob”, that still dominates teacher training in most – not quite all – universities does its best to ignore brain research, as it does not fit their goal of using education as a means of reshaping society, beginning with mixed-ability teaching. They would do better to put the evidence of brain research at the heart of their curriculum, and to investigate its application in each subject.

When this happens, the outcome is a happy and successful learning community in which issues of racism do not arise because the atmosphere of shared purpose and teamwork leaves no room for them.

As Katharine Birbalsingh put it on Any Questions:

“You should have seen my teachers on Monday. They were so thrilled. Everyone was beaming… One child who never smiles, and he beamed at me. We were all so excited to be back, and it is, it is lovely to be in school….”

Michaela staff had been working flat out during lockdown, with Zoom lessons – NEU please note – and other online content, but this was not an adequate substitute for school. “Children,” she said, “build a relationship with their teacher, that they have over the year, and that relationship is so important to that child, working hard and delivering for their teacher.”

This is also her solution to the issue of race. Britain, she says has perhaps only Canada as a competitor when it comes to “the best country in the world to live in with regard to race,” and this is one theme of her latest book, “The Power of Culture”. Children at Michaela sing patriotic songs and recite poems precisely to emphasise their full and active membership of society, in direct opposition to current campaigns that present them as victims. In the ten years since she stood up at our Conference and told the truth about the disintegration of education in London schools, Birbalsingh has endured marginalisation and insult – “Coconut” perhaps the most predictable – and has felt that she was swimming upstream. She is now so obviously correct that we may, to mix a metaphor, see the tide beginning to turn.

A footnote on the Huffington Post’s publication of a leaked draft of the DfE’s plans for September, including an apparent proposal to stop teaching some subjects. This is not the way to proceed. Focusing only on English, maths, and science will produce a boring grind, and not only for children whose interests lie in other directions. A better approach, as exemplified in Alex Quigley’s books, Closing the Vocabulary Gap and Closing the Reading Gap, is to build literacy and clear thinking into everything a school does, maximising brain activity and using school to build up the thinking power that highly educated parents develop in their children from birth. Schools that do this – see this 2005 report on Gateway School, Marylebone – close the gap. Those that don’t, perpetuate it.

Rob Sutton: Introducing the top 50 Conservative MPs on Twitter

29 Jun

Conservative MP Twitter power rankings: the top 50

Rob Sutton is an incoming junior doctor in Wales and a former Parliamentary staffer. He is a recent graduate of the University of Oxford Medical School.

Amongst the social media giants, Twitter is the primary battleground for political discourse. It’s also one of the key avenues by which MPs convey their message, and has near-universal uptake by members in the current House of Commons.

The effectiveness with which Twitter is utilised varies considerably between MPs, but it is difficult to compare like-for-like. How does one take into account the differences between, for instance, a freshman MP and a veteran Cabinet member? Length of service in Parliament and ministerial rank give a considerable advantage when building a following.

In this article, I have compiled a power ranking of MPs in the current Parliament, with the top 50 shown in the chart above. The MP’s follower count was adjusted by factoring in their previous experience, to better reflect the strength of their following and their success at engagement on the platform.

Being Twitter-savvy is about more than just a high follower count: any Secretary of State can achieve this just by virtue of the media exposure their office brings. Building a Twitter following based on thoughtful commentary and authentic engagement requires skill ,and can be achieved by members across all Parliamentary intakes and ranks of Government.

Though the top 10 is still dominated by MPs holding senior ministerial offices, the composition of the list beyond it is far more variable. A number of prominent backbenchers are in the top 20, and four members from the 2019 intake make the top 50, beating longer-serving and higher-ranked colleagues.

I hope that this list serves as recognition of the skill and contribution by Conservative members to public debate and engagement, beyond ministerial duties which so often dominate any mention in the media.

Building a model of Twitter power rankings

Success is judged by number of followers, with higher follower counts indicating greater influence on Twitter. The follower count was adjusted using three key parameters:

  • The number of years since an MP was first elected to Parliament.
  • The number of years the MP’s Twitter account has been active.
  • Their highest rank within Government achieved since 2010.

Higher values for each of these would be expected to contribute to a higher follower count. I built a model using the open-source Scikit-Learn package, and fitted it to data from the current Parliament.

The model was then used to predict how many followers a given MP might expect to have based on these three factors. The steps taken to produce a final “Twitter power score” were thus as follows:

  • Using these three factors, multiple linear regression was used to calculate the expected number of Twitter followers an MP might have.
  • Their true follower count was divided by the expected follower count to produce a single number which represented the MP’s performance at building a following.
  • Finally, a logarithm was taken of this ratio to make the number more manageable and to produce a final Twitter power score.

The final step of taking a logarithm means it is easier to compare between MPs without those who have very high follower counts (such as Boris Johnson) making the data difficult to compare, but it does not affect the order of the ranking.

Compiling the data

Having decided which factors to correct the model for, I collected the required information. All three factors were easy to find reliable sources for. The Twitter page for each MP displays the date the account was created, and the Parliamentary website provides the date of their first election to Parliament and previous government posts.

Members who are newly returned to the backbenches following governmental duties (such as Sajid Javid and Jeremy Hunt) are scored at their highest government rank since 2010 to recognise this. I was able to find the Twitter accounts and required information for 319 Conservative MPs who were included in this ranking.

To build a model based on this data required incorporating the highest government rank numerically. To do this, I assigned scores according to their rank. These grades recognised their relative seniority and media exposure associated with the office, with higher scores assigned to more senior positions:

  • Prime Ministers, Secretaries of State, Speakers, Leaders of the House and Chief Whips are scored 3.
  • Ministers of State, Deputy Speakers and Deputy Chief Whips are scored 1.
    Parliamentary Under-Secretaries of State, Parliamentary Private Secretaries and Whips are scored 0.5.
  • Backbenchers score 0.

When assigning these values, I considered the typical sizes of follower counts of MPs in each category. When comparing Secretaries of States to Ministers of State, the median follower count is around twice the size, but the mean follower count is around eight times the size, as a handful of very large follower count skews the results upwards.

Deciding on weightings requires a (somewhat arbitrary) decision as to which measures to use when comparing between groups, and the scores I decided on were ultimately chosen as a compromise across these different measures, which produced stable results when used in the model.

It is also worth explaining why Prime Ministers are grouped with Secretaries of State, despite the far higher media exposure and seniority of their post. When deciding on the respective weighting for different levels of government post, a sufficiently large pool of MPs was needed to produce a meaningful comparison. The only data points for comparison of Prime Ministers are Boris Johnson and Theresa May, so it is difficult to give them their own weighting without it being either unreliable or arbitrary.

While grouping them with Secretaries of State and other senior positions might be perceived as giving them an unfair advantage in the weighting, I felt it justified given these challenges in determining the “fair” weight to assign them. With this done, I had three parameters for each MP on which to build a model to calculate the expected number of Twitter followers.

Calculating the number of expected Twitter followers

I built a model to calculate the expected number of Twitter followers using the Scikit-Learn, a popular machine learning package in the Python programming language. The model used multiple linear regression to fit the input parameters to the known follower count.

The input data was prepared by removing extreme high outliers in the data which skewed the fit toward high numbers and away from the vast majority of MPs before fitting. Once fitted, an “expected value” of Twitter followers could be calculated for each MP, based on the year of their first election to parliament, the number of years on Twitter and their highest government rank since 2010.

Including more parameters increases the ability of the model to describe the difference between MPs’ follower counts (the variability). By increasing the number of input variables included in the model, more of the variability is captured:

  • One variable captures between 20.3 per cent and 36.1 per cent of the variability.
  • Two variables capture between 39.1 per cent and 43.1 per cent of the variability.
  • All three variables capture 48.7 per cent of the variability.

These three variables are therefore responsible for almost half of the variation between MPs in their follower counts. The remainder of the variability is likely due to a range of factors which the model does not include, of which the MP’s Twitter-savviness is of particular interest to us. I discuss these factors further below.

Limitations in the model

There are multiple other parameters which could be included in future iterations which I did not include in this model. In particular:

  • Membership or Chairmanship of Select Committees.
  • Previous election to a council, assembly, devolved legislature or the European Parliament.
  • Membership of the Privy Council.
  • Government positions prior to 2010.
  • Prominent positions within the Conservative Party, such as the 1922 Committee or European Research Group.
  • Twitter-savviness and effectiveness of their comms team.

Another limitation was not accounting for the perceived relative importance of various governmental departments: a Great Office of State or Prime Minister is scored the same as any other Secretary of State. The difficulties involved in ranking governmental departments were beyond this first model. The length of service in a given government post was also not considered.

Finally, the choice of model to fit the data may not be the optimal choice. Multiple linear regression assumes, per the name, that the distribution is linear. But the large outliers might be better described by a power law or Pareto distribution, or the non-linearities of a neural network.

During next week, ConservativeHome will produce profiles of six individual MPs who have performed notably well in the power rankings, and who reflect the contributions brought by members beyond their ministerial duties, if they have any.