Éoin Clarke’s blog has a post on the uneven geographical distribution of NHS cuts. He writes:
The wealthiest, and dare I say it Toriest, parts of England have actually experienced no job losses. The South East of England has actually grown its NHS workforce since the May General Election, while the North West of England alone has experienced more than 6,500 job losses.
His post includes a chart. Clarke’s chart shows absolute figures – I thought I’d make my own version of it, showing percentage change. This doesn’t make any real difference to the story, but here it is anyway. Note that these figures are Hospital and Community Health Service staff, excluding primary care staff – lots of NHS employment isn’t captured.
The mathematics of inferential statistics is based on the logic of random sampling: the inferences we make in inferential statistics work on the assumption that the data we are inferring from is randomly sampled from the population we are inferring to – that every member of the population has an equal chance of ending up in our dataset. Obviously this usually isn’t the case; but that’s the assumption, and the further our actual sampling practice deviates from that ideal situation, the less likely our inferences are to have any validity.
In much inferential statistics, the population we are sampling from is an actual population of cases, which could in principle be observed directly if we only had the money, time, staff, access, etc. etc. Here the ideal situation is to create a sampling frame that lists all the cases in the population, randomly select a subset of cases from the sampling frame, and then collect data from those cases we’ve selected. In practice, of course, most data collection doesn’t work this way – instead researchers pick a convenience sample of some kind (sometimes lazily, sometimes unavoidably) and then try to make the argument that this sampling method is unlikely to be strongly biased in any relevant way.
Sometimes, however, the population from which we draw our sample is not an actual population of cases that happen for contingent practical reasons to be beyond the reach of observation. Sometimes the population from which we draw our sample is a purely theoretical entity – a population of possible circumstances, from which actuality has drawn, or realised, one specific instance. Thus our actual historical present is a ‘sample’ from a ‘population’ of possible realities, and the generalisations we aim to make from our sample is a generalisation to the space of possibilities, rather than simply to some aspect of crass and meagre fact.
When we make claims that are predictive of future events, not merely of future observations of present events, we are, tacitly or overtly, engaged in this endeavour. To predict the future is to select one possible reality out of a space of possibilities, and to attribute a likelihood to this prediction is to engage in the statistical practice of assigning probability figures to a range of estimates of underlying population parameters – or, equivalently, to give probability figures to a range of estimates of future sample statistics ‘drawn from’ that underlying population. I may try to articulate this point with more precision in a future post – I’d like to spend more time on Bayesian vs. frequentist approaches to probability. And there is, of course, a ‘metaphysical’ question as to whether such a ‘population’ ‘really exists’, or whether the ‘samples’ themselves are the only reality, and the ‘population’ a speculative theoretical entity derived from our experience of those samples. Functionally, however, these stances are identical: and by my pragmatist lights, to note such functional equivalence is to collapse the two possibilities together for most theoretical purposes.
When we speak of universal natural laws, then, we are stating that a given fact – the law in question – will be true in the entire range of possible worlds that might, in the future, be actualised in reality. (Whether this ‘possibility’ should be understood in ontological or epistemological terms is beside the point). For some, it is the role of science to make such predictions: on this erroneous stance, science attempts to identify universal features of reality, and any uncertainty that accrues to scientific results is the uncertainty of epistemological weakness, rather than ontological variation. Here, for example, is a video of Richard Feynman making fun of social science for its inability to formulate universal laws of history:
To take this attitude is to misunderstand the nature not just of social science, but of science in general. Science is not characterised by a quest for certainty or for permanence, but is rather characterised by an ongoing collective process of hypothesis formation and assessment, based on specific collectively accepted evidentiary standards. The conclusions of science cannot be certain, because they must always be vulnerable to refutation in the light of empirical evidence and the application of community norms of argument. Similarly, the phenomena examined by science need not be necessary, or even ongoing. A scientific endeavour can be entirely descriptive, of the most local and variable phenomena imaginable, so long as the process of description is subject to the appropriate communal evidentiary norms. It can, similarly, be explanatory without being predictive, for we can analyse the causes of the phenomena we observe without being able reliably to predict those causes’ future impacts and interactions. The set of phenomena regarding which long-term or even short-term reliably predictive hypotheses can be formed is smaller than the set of phenomena that can be studied empirically using the relevant community norms of hypothesis formation and assessment.
The social sciences often approach this limit case of the purely descriptive. Social reality is enormously variegated – and often there is little in the way of testable general claims that can be taken from a study of any given social phenomenon. But prediction is nevertheless sometimes the goal of social science. When the social sciences aim to study social phenomena, the ‘laws’ they aspire to uncover are always local and limited in scope – and when we form a hypothesis, this hypothesis applies within a certain local limit and no further. Where to draw the line – where to locate this limit – is a qualitative question that the community of social scientists must always bear in mind, but the existence of this limit in no way renders the endeavour ‘unscientific’.
When we make a social-scientific prediction, then, we are making a claim about what future reality will drawn from the space of possibility. We do not know the scope of this space – nor do we have any reason to regard the principle of selection as random or unbiased – indeed, we have strong reasons to believe the contrary. Further, the nature of social reality is such that we can and do aspire to intervene in this selection – to attempt to influence what possibilities are realised. As social scientists we sometimes aim to predict what outcomes will be drawn from this space of possibilities – and such a prediction can only be made within the framework of a broader, historically informed judgement of the narrower space, within the space of possibilities, that we aspire to model.
But we should also be aware of other, unrealised but potentially realisable social possibilities, beyond the set of possibilities we are modelling at any given moment. Part of the function of the scrupulous social scientist is to describe this space of possibilities itself – to describe not just regularities, but also the possible variety from within which those local regularities are drawn. We cannot know the limits to the space of possibilities – no sampling frame of possible societies exists. But we can explore what the ‘samples’ themselves – existing and historical societies and behaviours – tell us about the scope of that hypothetical space.
This latter task is where social science intersects with political practice. The understanding of the likely behaviour of social reality is important for political practice – but so too is a sense of the larger space of possibilities from which our own past and present societies have been drawn, and from which alternative futures could be drawn, or made, if we only had the political ability to do so.
Alfie Meadows, a philosophy student at Middlesex University, was struck as he tried to leave the area outside Westminster Abbey during last night’s tuition fee protests, his mother said.
After falling unconscious on the way to Chelsea and Westminster Hospital, he underwent a three-hour operation for bleeding on the brain.
Susan Meadows, 55, an English literature lecturer at Roehampton University, said: “He was hit on the head by a police truncheon. He said it was the hugest blow he ever felt in his life. The surface wound wasn’t very big but three hours after the blow, he suffered bleeding to the brain. He survived the operation and he’s in the recovery room.”
But nothing can stop the liberal press, all aflutter at paint thrown at the Rolls Royce carrying the heir to the throne, from compliantly propagandising for the police and the ruling coalition. The “violence” in question here is not the hospitalisation with internal bleeding requiring a three hour operation of a 20-year-old, but paint thrown at a car. From the same page in the Guardian as that which covers the brutal and unprovoked attack by armed agents of the state on a 20-year-old student exercising his right to protest, we have this:
It would be silly as well as cynical to imagine that David Cameron is privately pleased to see public indignation so easily deflected from his government’s controversial policy. Or that Nick Clegg is positively thrilled to have a day off from his new constitutional role as air raid shelter for the Tories.
Why? Because they’re not wicked or stupid. Trouble on the streets means political trouble and ill-affordable expense for the coalition. Two thousand coppers on overtime cost money.
Oh who will think of the Metropolitan Police’s payroll department?
I’ve been reading Mannheim’s Ideology and Utopia, and I’ve found his schematisation of different political ideologies in the third essay, Prospects of Scientific Politics, to be extremely helpful. Basically Mannheim categorises ideologies by their understanding of the relation between political practice and history. Here are his categories:
1. Bureaucratic conservatism
Reduces political problems to problems of administration, and thereby obscures the political construction and function of the socially specific organisational framework bureaucratic decision-making requires. Order is the highest political value; the organisation of a specific bureaucracy is equated with order in general; challenges to the bureaucratic framework are understood as deviations from order, and quashed.
2. Conservative historicism
Understands politics in terms of the dichotomy between deliberate planned construction (bad), and natural organic development (good). That which is not deliberately politically planned is understood and valued, romantically, as natural and organic. (Classic example: Burke.)
3. Liberal-democratic bourgeois thought
Sees public-sphere political debate as the medium by which the correct ends of politics can be a) decided upon and b) achieved. Democratically elected parliament is the enabling institution in which competing social interests can mediate their conflicts via debate. This can presumably come in a stronger form, oriented towards unified rational consensus, and a weaker form, oriented towards ongoing pluralistic negotiation.
4. The socialist-communist conception
Sees contests between conflicting political viewpoints and communal interests as unresolvable via public-sphere discourse. The appropriate sphere of political action is therefore not, or not just, parliamentary democracy, but also mass activism and organisation, ultimately oriented towards revolution. (Mannheim understands revolution as aimed at realising a rational organisation of society that cannot be achieved by rational persuasion.)
5. Fascism
The central concept of political action is the ungrounded or self-grounding deed; the central political actors are an elite of superior individuals. Those who are not members of the elite should be unconditionally subordinate to their elite leader(s). Unlike vanguardist communism, where revolutionary leaders are understood as channelling the will of the masses, in fascism the masses are understood as channelling / subordinate to the will of the leader. Political programmes are unimportant – what matters is self-realising action (of the elite).
