Theme: Education

  • Updating English Spelling? Not so fast, maybe.

    For some reason, Joseph Fouche from The Committee On Public Safety found a proposal on revising English Spelling interesting enough to write about. He lifts this example:

    It woz in the ferst dae ov the nue yeer that the anounsment woz maed, aulmoest simultaeneusli from three obzervatoris, that the moeshen ov the planet Neptune, the outermoest ov aul the planets that w(h)eel about the sun, had bekum very eratik. A retardaeshen in its velositi had been suspekted in Desember. Then a faent, remoet spek ov lyt woz diskuverd in the reejen ov the perterbd planet. At ferst this did not cauz eni veri graet eksytment. Syentifik peepl, houever, found the intelijens remarkabl enuf, eeven befor it becaem noen that the nue bodi woz rapidli groeing larjer and bryter, and that the moeshen woz kwyt diferent from the orderli proegres ov the planets…

    For some other reason known only to those of us who are social science nerds, I felt the need to respond. Possibly because I am a conservative by nature. Possibly because I understand as an economist, the value of CAPITALIZING just about everything. And that language is a form of capital that can either amplify or discount human beings that use it. SPELLING IN ENGLISH CONVEYS INFORMATION The odd spelling certainly makes the language harder to learn but conveys with it much greater content, and it solves the problem of homonyms (words that sound the same but have different meanings) and context. Complex spellings approach abstract symbols that reduce the problem of defining context with similar sounds. All those spellings and oddities convey information. That information is useful. THERE IS NO REASON THE FUTURE OF WRITTEN LANGUAGE IS CONSONANTAL It might be better to see it as an advantage for a very complex language to approach becoming both phonetic and pictographic rather than purely phonetic. (Which is what has happened with english.) Imagine chinese by contrast, which is a very old language, and is constructed of a myraid of homonyms and complex tones. (languages start with clicks in the ancient past and end with tonal songs in the distant future.) There are only 30K images or words. Not the nearly 1M in english. They speak poetically because they can’t be more precise. It’s an old language but a primitive one. English, the germanic indo european languages in particular, are technical languages. They are the languages of craftsmen and soldiers: meant to convey precision. LANGUAGES CONTAIN METAPHYSICAL JUDGEMENTS Try to speak probabalistically in Spanish. Try to speak factually in polish. Try to eliminate emotional experience from Romanian or italian. Try to convey duty in the Slavics. Languages are more than sounds. They are complex constructs that frame and limit as well as amplify, different social ideas. English is wonderful for insulting someone’s intelligence. Eskimo is wonderful for describing weather. Talk about sex or emotional experience in italian or french. See other languages for what they are: vastly primitive. THE ECONOMICS OF WRITING ARE CHANGING Another argument might be, that we are rapidly approaching a position where reading and writing, which are very abstract very inexpensive forms of illustration, may be irrelevant to more than half of the population: where the future is most likely constructed of pictograms or videograms – moving illustrations that are constructed by and presented by machines. The only reason we use letters rather than images is that they are less expensive to produce. Especially for consonantal languages. However, as languages mature (which they are doing rapidly right now) they become lazy and tonal rather than consonantal. And our current symbolic representations of those languages with consonantal symbols that do NOT convey tones is limiting to representing the tonal. And while the above statement may seem economically impossible, because of the current perception of machines as expensive, we must remember that writing materials were as expensive in the past, during the development of writing, as we consider computers today. Today’s iPad is yesterday’s quill and parchment. LUDDITES ARE EVERYWHERE Effectively the author is promoting a pidgin: a language for simple people to hold simple conversations, rather than a language for conveying complex information. As such, he is, like many others, a Luddite. And luddites are searching for a simpler past rather than a complex, safer, and more prosperous future. And we do not need to dumb down our civilization any further. Even if it does make reading easier. Learning to read a hard language if it conveys greater information increases human capital. 🙂

  • Higher social classes have a significantly higher average IQ than lower social classes

    Reposted here for reference.

    Social class IQ differences and university access By Bruce G Charlton A feature for the Times Higher Education – 23 May 2008 Since ‘the Laura Spence Affair’ in 2000, the UK government has spent a great deal of time and effort in asserting that universities, especially Oxford and Cambridge, are unfairly excluding people from low social class backgrounds and privileging those from higher social classes. Evidence to support the allegation of systematic unfairness has never been presented, nevertheless the accusation has been used to fuel a populist ‘class war’ agenda. Yet in all this debate a simple and vital fact has been missed: higher social classes have a significantly higher average IQ than lower social classes. The exact size of the measured IQ difference varies according to the precision of definitions of social class – but in all studies I have seen, the measured social class IQ difference is substantial and of significance and relevance to the issue of university admissions. The existence of substantial class differences in average IQ seems to be uncontroversial and widely accepted for many decades among those who have studied the scientific literature. And IQ is highly predictive of a wide range of positive outcomes in terms of educational duration and attainment, attained income levels, and social status (see Deary – Intelligence, 2001). This means that in a meritocratic university admissions system there will be a greater proportion of higher class students than lower class students admitted to university. What is less widely understood is that – on simple mathematical grounds – it is inevitable that the differential between upper and lower classes admitted to university will become greater the more selective is the university. *** There have been numerous studies of IQ according to occupational social class, stretching back over many decades. In the UK, average IQ is 100 and the standard deviation is 15 with a normal distribution curve. Social class is not an absolute measure, and the size of differences between social classes in biological variables (such as health or life expectancy) varies according to how socio-economic status is defined (eg. by job, income or education) and also by how precisely defined is the socio-economic status (for example, the number of categories of class, and the exactness of the measurement method – so that years of education or annual salary will generate bigger differentials than cruder measures such as job allocation, postcode deprivation ratings or state versus private education). In general, the more precise the definition of social class, the larger will be the measured social class differences in IQ and other biological variables. Typically, the average IQ of the highest occupational Social Class (SC) – mainly professional and senior managerial workers such as professors, doctors and bank managers – is 115 or more when social class is measured precisely, and about 110 when social class is measured less precisely (eg. mixing-in lower status groups such as teachers and middle managers). By comparison, the average IQ of the lowest social class of unskilled workers is about 90 when measured precisely, or about 95 when measured less precisely (eg. mixing-in higher social classes such as foremen and supervisors or jobs requiring some significant formal qualification or training). The non-symmetrical distribution of high and low social class around the average of 100 is probably due to the fact that some of the highest IQ people can be found doing unskilled jobs (such as catering or labouring) but the lowest IQ people are very unlikely to be found doing selective-education-type professional jobs (such as medicine, architecture, science or law). In round numbers, there are differences of nearly two standard deviations (or 25 IQ points) between the highest and lowest occupational social classes when class is measured precisely; and about one standard deviation (or 15 IQ points) difference when SC is measured less precisely. I will use these measured social class IQ differences of either one or nearly two standard deviations to give upper and lower bounds to estimates of the differential or ratio of upper and lower social classes we would expect to see at universities of varying degrees of selectivity. We can assume that there are three types of universities of differing selectivity roughly corresponding to some post-1992 ex-polytechnic universities; some of the pre-1992 Redbrick or Plateglass universities (eg. the less selective members of the Russell Group and 1994 Group), and Oxbridge. The ‘ex-poly’ university has a threshold minimum IQ of 100 for admissions (ie. the top half of the age cohort of 18 year olds in the population – given that about half the UK population now attend a higher education institution), the ‘Redbrick’ university has a minimum IQ of 115 (ie. the top 16 percent of the age cohort); while ‘Oxbridge’ is assumed to have a minimum IQ of about 130 (ie. the top 2 percent of the age cohort). *** Table 1: Precise measurement of Social Class (SC) – Approx proportion of 18 year old students eligible for admission to three universities of differing minimum IQ selectivity Ex-poly – IQ 100; Redbrick – IQ 115; Oxbridge IQ 130 Highest SC– av. IQ 115: 84 percent; 50 percent; 16 percent Lowest SC– av. IQ 90: 25 percent; 5 percent; ½ percent Expected SC diff: 3.3 fold; 10 fold; 32 fold Table 2: Imprecise measurement of Social Class (SC) – Approx proportion of 18 year old students eligible for admission to three universities of differing minimum IQ selectivity Ex-Poly – IQ 100; Redbrick – IQ 115; Oxbridge – IQ 130 Highest SC –av. IQ 110: 75 percent; 37 percent; 9 percent Lowest SC –av. IQ 95: 37 percent; 9 percent; 1 percent Expected SC diff: 2 fold; 4 fold; 9 fold *** When social class is measured precisely, it can be seen that the expected Highest SC to Lowest SC differential would probably be expected to increase from about three-fold (when the percentages at university are compared with the proportions in the national population) in relatively unselective universities to more than thirty-fold at highly selective universities. In other words, if this social class IQ difference is accurate, the average child from the highest social class is approximately thirty times more likely to qualify for admission to a highly selective university than the average child from the lowest social class. When using a more conservative assumption of just one standard deviation in average IQ between upper (IQ 110) and lower (IQ 95) social classes there will be significant differentials between Highest and Lowest social classes, increasing from two-fold at the ‘ex-poly’ through four-fold at the ‘Redbrick’ university to ninefold at ‘Oxbridge’. Naturally, this simple analysis is based on several assumptions, each of which could be challenged and adjusted; and further factors could be introduced. However, the take-home-message is simple. When admissions are assumed to be absolutely meritocratic, social class IQ differences of plausible magnitude lead to highly significant effects on the social class ratios of students at university when compared with the general population. Furthermore, the social class differentials inevitably become highly amplified at the most selective universities such as Oxbridge. Indeed, it can be predicted that around half of a random selection of kids whose parents are among the IQ 130 ‘cognitive elite’ (eg. with both parents and all grandparents successful in professions requiring high levels of highly selective education) would probably be eligible for admission to the most-selective universities or the most selective professional courses such as medicine, law and veterinary medicine; but only about one in two hundred of kids from the lowest social stratum would be eligible for admission on meritocratic grounds. In other words, with a fully-meritocratic admissions policy we should expect to see a differential in favour of the highest social classes relative to the lowest social classes at all universities, and this differential would become very large at a highly-selective university such as Oxford or Cambridge. The highly unequal class distributions seen in elite universities compared to the general population are unlikely to be due to prejudice or corruption in the admissions process. On the contrary, the observed pattern is a natural outcome of meritocracy. Indeed, anything other than very unequal outcomes would need to be a consequence of non-merit-based selection methods. Selected references for social class and IQ: Argyle, M. The psychology of social class. London: Routledge, 1994. (Page 153 contains tabulated summaries of several studies with social class I IQs estimated from 115-132 and lowest social classes IQ from 94-97). C.L. Hart et al. Scottish Mental Health Survey 1932 linked to the Midspan Studies: a prospective investigation of childhood intelligence and future health. Public Health. 2003; 117: 187-195. (Social class 1 IQ 115, Social class V IQ 90; Deprivation category 1 – IQ 110, deprivation category 7 – IQ 92). Nettle D. 2003. Intelligence and class mobility in the British population. British Journal of Psychology. 94: 551-561. (Estimates approx one standard deviation between lowest and highest social classes). Validity of IQ – See Deary IJ. Intelligence – A very short introduction. Oxford University Press 2001. Note – It is very likely that IQ is _mostly_ hereditary (I would favour the upper bound of the estimates of heredity, with a correlation of around 0.8), but because IQ is not _fully_ hereditary there is a ‘regression towards the mean’ such that the children of high IQ parents will average lower IQ than their parents (and vice versa). But the degree to which this regression happens will vary according to the genetic population from which the people are drawn – so that high IQ individuals from a high IQ population will exhibit less regression towards the mean, because the ancestral population mean IQ is higher. Because reproduction in modern societies is ‘assortative’ with respect to IQ (i.e. people tend to have children with other people of similar IQ), and because this assortative mating has been going on for several generations, the expected regression towards the mean will be different according to specific ancestry. Due to this complexity, I have omitted any discussion of regression to the mean IQ from parents to children in the above journalistic article which had a non-scientific target audience.

  • Comparing Medical, Technical, Educational, and Political Testing Methodologies

    There was a great deal of research and discourse on technology in medicine when computing systems began to enter the operating room in the 1990’s. In particular, in the use of anesthesia. The most commonly discussed example was a difference in turning knobs, in which one machine turned right to increase and another turned left to increase, and in confusion the patient was killed. This and other events caused a systemic review of medical equipment and the development of standards. THe emphasis in the medical community however, was just as directed at training it’s staff as it was at the hardware. This has not been the case in IT, largely because costs of risk are more easily assumed, and costs of failure are perceived as more tolerable. However, this tolerance is due in large part to a lack of visibility by executive management, to the breadth and impact of those risks, partly because of a lack of understanding of business risk measure by IT management, and in many businesses a failure of IT and Accounting and Finance to share sufficient information for IT to do so. The medical and engineering fields attempt to solve the problem of risk and recovery differently. They do so because of biases. Those biases evolved from the methodology and traditions of the culture of the profession. There is a tendency to think that IT has fully commoditized and therefore can be regulated as is plumbing and electricity, but IT is far closer to medicine in it’s complexity than are the more mechanical traditions. And this confusion, or error in philosophy is common within many different specializations or social groups. From technical specialties to the philosophical biases of entire civilizations. The medical field, especially in surgery and hospital care, includes infinite risk (people die, and there is a high liability cost) and consists of actions are taken by people using tools. This set of properties has made their industry focus on the human element: on improving people, and in particular, on the assumption of failure, therefore improving people. In medical devices, there is an extraordinary emphasis (due to research papers) on producing tools with very consistent user interfaces that are extremely simple and consistent (such as dials turning the same direction producing similar results) and an emphasis on protocol (scripts that are followed), and lastly on training people to use these tools in order to reduce failure. But every process is seen as a human problem of discipline and training. Not of engineering at lower cost, or productivity — but as risk reduction. Production costs are far lower than the costs of failure. This is true for the military as well, where vast numbers of people must work in extraordinarily deadly conditions, under extreme duress and exhaustion, using complex and dangerous tools. Soldiers are taught very simple behaviors, one of which is to speak entirely in facts, rather than interpretations – one of the primary purposes of western basic training. To teach soldiers to separate opinion from recitation of observation. Similarly, when it was found that different hierarchical social structures around the world prohibited airline crews from communicating effectively and was causing deadly crashes, these crews were taught english and declarative mannerisms by training specifically to overcome these cultural biases and lack of clarity in communication –which is why english is the language of transportation. English contains a spoken protocol of clarity which english speakers do not understand, just assume, and that clarity originated in the western military tradition of enfranchising all citizens in a militia. Epistemology. This is a word meaning, in practice, ‘the study of how we know what we know’. Every field has an assumed epistemology. Teaching, Soldiers, Politicians, Engineers, Plumbers, and even psychologists, have a means of understanding causality, and a means of testing themselves. Because each field is limited and includes different kinds of risk and failure, people use different testing criteria for planning and choosing their actions. Teachers for example over rely on written tests rather than question and answer, and therefore test most often for short term memory rather than understanding. This has consequences for all societies, but largely for our political system which relied on rhetorical ability. Protestant churches in the colonial period were effectively debating forums for local social solutions — something that is required of a democratic system. Furthermore, another consequence of teaching methods, that attempts to reduce costs, is that of literally destroying boys minds (physical damage to the brain development) by making them sit for hours a day. (Or by the use of drugs to cause similar brain damage.) This destroys society in doing so, because while girls learn to cooperate through compromise, men learn to cooperate through displays of competition and experimentation with dominance, and if prevented from doing so they will not develop a interest in the real world, fail to take responsibility and have little interest in society. All because of the epistemology of teachers, in an effort to perform ‘efficiently’. (And as fathers they will play world of Warcraft, not because they want to but because during their development they were forcibly harmed by these teachers.) Doctors do not make these kinds of errors. Because the cause and effect of their actions are visible. The cause and effect of political policy, in particular, monetary policy, is likewise opaque, and politicians seek to keep it so. Fire regulations are fascinating, and building codes in particular, because of how few office building fires we have. The cost of construction is heavily influenced by these codes, and has dramatically risen, and both regulations and costs continue to expand despite the fact that they appear no longer to reduce risk. Conversely, firemen still drill and practice on a regular basis which is good, but we still allow tall buildings to be constructed despite the fact that it is dangerous to put many people in a building of more than six stories, that it creates congestion, and in general, research is conclusive, that people don’t like working in them, and that they are unhealthy environments, and heat dissipators and energy consumers. Effective military organizations run drills. Lots of them. The US in particular runs them constantly. Some NATO countries (Hungary) by contrast only allow their soldiers to shoot one to three bullets in all their basic training in order to reduce costs. But in practice, these organizations are symbolic in nature and are incapable of fighting. Partly because fighting in adverse conditions is largely dependent upon the relationships between soldiers built through shared experiences. People are not that smart IN time, but fairly smart OVER time. We can solve problems given time. The only way to reduce the time, which is equivalent to cost, of recovery from failure is to pre-compute, or pre-train people to recover from failure, and in particular in the process of discovering how to recover from failure. If IT management applied the same discipline, they would, once a quarter, create a scenario where three or more elements of their systems failed within a short period, and the staff had to recover from it. This is the approach most military tacticians take to educating their people. There is too often an emphasis on the efficient achievement of goals, rather than on giving people goals and inserting ‘lessons’, or hurdles and obstacles for them to overcome. In IT engineering, risk is rarely stated, because it is rarely visible, despite the catastrophic cost to business. Errors are considered to be functions of the machinery, rather than of the people using and maintaining it. People are considered a cost to be minimized so that more work can be put through them. If a system cannot be assembled and disassembled and tested at every point in the process, then the people cannot understand how to recover it under duress. This mastery by intentional reconstruction is how Formula One racing teams think of the process of engineering. They constantly drill, because of the value of time in racing. IT is this value of time, and its lost productivity cost, that is hidden by IT. furthermore, IT does not report on the problems it solved and the cost of those problems sufficiently to keep management informed and educated on risks. THe converse happens as well, which is that IT is a resistance to change, because the impact of that change is something they don’t understand, because they have spend too little time in drills. Some companies are constantly fighting this battle. Citicorp for example, was a cluster of different banks under one management system and brand name, but not under one infrastructure (I hope I have the bank right here, I am pulling from memory). This meant that in the financial crisis, it was less able to react, because they kept costs down by keeping risk high, by not developing a common infrastructure, both technologically and organizationally. Doctors have extraordinary peer reviews post success and post failure. They spread knowledge by discourse and question and answer. (Part of this is the skill of medical students in analytical thinking and rhetoric versus that of the IT population.) However, the concept of improving people thorough discourse is consistent in their approach. Each patient is a new experiment, having the potential for failure or success and the consequential new learning that comes from either. Retail shops use secret shoppers to test for shoplifting and customer service. The military uses maneuvers, and even uses it’s own members to test it’s own security. IT rarely conducts planned failures. To see how the staff reacts and to educated them. IT does perform upgrades. And for this reason, upgrades and system maintenance are one of the most important means of keeping the staff trained, because they fulfill as similar function to drills and teach the value of redundancy. These assumptions, this epistemology, is different for every little field of specialization. But what happens in each field is that they in turn confuse the methods, practices, tools, means of testing, and general operating philosophy then become assumptions about the nature of the real world, and assumptions about human nature, and even human capability, and in particular human plasticity and adaptability, as well as human learning and understanding. WHen in fact, we must first understand the human animal as the maker and maintainer of complex systems, and that the human animal has very specific properties, none of which are terribly impressive without extraordinary role playing, testing and training in real world (versus written or spoken) conditions, where, they must cooperate toward complex ends, in real time, under conditions of duress. For example, human civilizations are different largely because social orders were initially established by their warriors and their battle tactics. It may seem odd that the east, west, steppe, desert, and mystical civilizations all are caused (Armstrong, Keegan) . It is uncommon that even westerners understand that western battle tactics in europe were heavily based on maneuver (chariots) the required cooperation. Cooperation required political enfranchisement, political enfranchisement led to equality, equality led to debate, debate led to logic, logic led to science and rationalism. This is different from both the tribal raiders, the mystical zoroastrian as well as the chinese familial and hierarchical traditions. An interesting problem for intellectual historians has been why Confucius could not solve the problem of politics and directed the civilization to familial structures instead. Or that the primary difference between east and west is the assumption that our job is to leave the world better than we entered it, that the purpose of man is to transform the word for his utility, that man is the ultimate work of nature, versus the eastern view that our job is to work in harmony with the world, (non-disruption), that humans are somewhat vile by nature, that man is necessarily in class structures, and that truth is less important than the avoidance of conflict (except when it involves barbarians). These differences led to our different concepts of life itself. In IT there is a cultural assumption that the engineers job is to prevent failure, or, to work with the systems without causing additional complexity that increases the probability of failure, or to repair from failure. However, few organizations are structured such that there are drills, and processes by which to recover from failure for the entire purpose of educating the human element in the system. This cultural legacy is largely due to the perceived (although not factual) high cost of IT implementations, largely as a remnant of the fact that during IT’s development, a great deal of research and development, in pursuit of competitive advantage, was conducted in-house, with the resulting failure of research and development programs. In fact, IT infrastructure costs were significantly lower than many previous innovative technologies adapted by business. (In particular, electricity as a replacement for steam or water power.) And by comparison, the calculative burden an uncompetitiveness placed upon companies by antiquated accountancy methods, or government taxation programs, or building codes, are often higher than IT costs. In Europe for example (as well as in California) businesses for small networks, rather than more efficiently combine into larger organizations with lower administrative costs, just to avoid these external expenses. So, this is not only an IT problem, but an executive management problem: the CEO cannot authorize budget for risk mitigation, (nor cover himself by doing so) if the IT management does not understand and quantify the risk, or it’s probability. ( If Executive management does not promote better methods once presented with the information, then the popular revolt is the only real solution (go work somewhere more worthy of your talents that doesn’t reduce it’s cost of doing business by counting on the fact that you’ll live under greater unnecessary stress, and possibly lose sleep and health, or even risk your job, because you were not allowed to engage in preventative activities. Conversely, if you dont provide them with that knowledge, in form and quality at least equal to those provided by sales and accounting organizations then they are not to blame for your inability to do so. They have an epistemology too: which is that they are told many things by many people, and must be able to test these bits of gossip and opinion somehow and only numbers can provide that ability.) IT management has long been criticized for wanting a seat at the table, but not warranting a seat at that table. (Nick Carr) But in general, these people may understand the craft, but often fail to understand the metrics and management of capital in a business, In other words, executives are included for their ability to postulate theories and deliver results. Customer service internally and externally, Risk (Failure Management), Productivity Contribution by the improvement of competitiveness, and Cost OF SErvices, are all criteria by which IT organizations should be measured. From the “ultimate question” for customer service, to cost of service, all of these are measurable. But you cannot judge that service if the management does not adequately measure it, and report on it, so that the executive management of the organization is capable of understanding and making decisions that support IT’s mission. Think of how much information the Accounting (history) and Finance (future) organization gives to the CEO. THink about how much the Sales organization gives to the CEO. THink of how LITTLE marketing organizations tend to give by comparison, and think of how much less than marketing, the IT organization gives. The respect and influence that a function of the company has over the distribution of resources in the company has largely to do with the metrics that it provides the management team. And how much exposure to risk the IT organization inserts into the business by failing to see the management of complex systems as one of engineering rather than one of human development and the testing of humans for failure, and the measurement of humans in their ability to recover from failure. Just as public intellectuals try to change public opinion to influence policy, by the use of narrative and argument, as well as data and it’s interpretation, because they need to help people think differently who have previous intellectual assumptions and biases dependent upon the methods and tools that they use in daily life and then apply outside of that domain of experience, IT management, and to some degree, the staff, must look at the underlying assumptions both in IT and in general business management and develop the discipline internally to experiment with failure, in order to teach the human component of complex systems, how to react in short time periods, while at the same time, using metrics and measures to inform the policy makers in executive management, so that they can intelligently and rationally make decisions about the allocation of resources for the purpose of creating profit (a measure of our use of the world’s resources), and the reduction of risk, so that all members of the organization, who are choosing to invest in this stream of income and friendships and knowledge at this organization, instead of an alternative stream of income, friendships and knowledge at another organization, can reduce the risk and cost to themselves in the event of failure of those estimates of risk. It’s all economics after all.

  • is working on this year’s initiatives

    is working on this year’s initiatives, a philosophy of marketing, and a philosophy of empathy


    Source date (UTC): 2009-01-20 08:59:00 UTC