What struck me most upon reading this was the inherent contradiction in his position, a contradiction echoed by many who call themselves Libertarians.  On the one hand, Hockey claims to be inspired by the work of Mill, most notably his argument that collective power should only be used against the individual to prevent harm to others.  Interestingly, he cautions against the growth in state power and argues that the subversion of individual rights that occurred under the Howard government of which he was a minister should be rescinded as quickly as possible.

Yet on the other hand, Hockey rallies against a Bill of Human Rights for Australia, arguing that it will imbue the Judiciary with too much power and undermine the independence of the courts.  Judges, he argues, will be making political, not legal decisions and this is undemocratic. This position is contradictory on a number of counts however.

The Judiciary exists in part to provide a check against the power of the Legislature.  They are the safety value that helps ensure the Libertarian ideals of Mill are not consumed by an overreaching State.   They have always interpreted laws and made decisions on contestable issues that some in the legislature disagree with.  Far from being undemocratic, a Judiciary that is able to declare laws passed by Parliament unconstitutional lies at the very heart of our democracy.

Contrary to what some may think, the Judiciary do not make laws – that power is limited to Parliament.  If Hockey is concerned about Judges making contestable decisions about conflicting human rights, then the issue lies in the contents of a Bill of Rights, not in the existence of a Bill itself. As a Member of Parliament, this problem is wholly within Hockey’s power to solve.

Individual rights can only be protected by the law. They must be made explicit if their protection is to be enforced.  A Bill of Human Rights, one that explicitly documents our fundamental rights and freedoms, only serves to enhance the Libertarian ideals that Hockey espouses. The individual freedoms and rights that he holds so dear will only be strengthened by a formal Bill of Human Rights explicitly stating what they are and a strong Judiciary that can enforce them.

• Perfect for multi-user CMS.
• No more unwanted WP Developer Feeds or inbound links!
• Individual dashboard widget control.

Installation

1. Upload `dashboard-heaven` directory to the `/wp-content/plugins/` directory
2. Activate the plugin through the ‘Plugins’ menu in WordPress
3. In the Admin panel, go to Tools => Dashboard Heaven

Requirements

• Developed for WordPress 2.9.2
• Tested on Version 2.9.9

The filter that needs to be called to edit the user profile details is user_contactmethods…

add_filter( ‘user_contactmethods’ , ‘update_contact_methods’ , 10 , 1 );

In your callback function (in this example ‘update_contact_methods’), use the following code to add a new field or remove an existing one.

$contactmethods['new_field'] = ‘New Field Name’;

unset($contactmethods['old_field_name']);

The beauty of this new functionality is that the profile data is stored in the wp_usermeta table and can then be accessed anywhere in your theme by calling get_usermeta( $user_id ,  $meta_name ).

So putting it all together, add the following code to your template’s functions.php file…

add_filter( ‘user_contactmethods’ , ‘update_contact_methods’ , 10 , 1 );

function update_contact_methods( $contactmethods ) {

// Add new fields
$contactmethods['phone'] = ‘Phone’;
$contactmethods['mobile'] = ‘Mobile’;
$contactmethods['address'] = ‘Address’;

// Remove annoying and unwanted default fields
unset($contactmethods['aim']);
unset($contactmethods['jabber']);
unset($contactmethods['yim']);

return $contactmethods;
}

There you have it, a clean and simple way to customise your user profile information

While death and injury from violent acts is truly terrible, it is the change in behaviour of those not directly affected that damages our society and way of life the most.  Like most editorials, the Australian highlights the inadequacies in our current security arrangements that allowed this failed bombing to happen and notes a range of immediate security changes like full body pat downs on flights to the US. If we’d only done this sooner the argument goes, we could have averted this near tradjedy.

But sadly, it is in our response to terrorism where terrorists truly succeed.  Whilst terrorists acts result in fewer deaths and injuries than from peanuts, lightning strikes and accident causing deer, our legal and behavourial changes have been enormous.  We’ve changed the way we travel and move freight at enormous cost to the economy. We declare an emergency and arrest people when they get sick and spend too long in the toilet. We’ve given up civil liberties and long held human rights, all to reduce the threat of terror, but are yet to declare a War on Peanuts or include Bambi in the ‘Axis of Evil’.

Perhaps the objective of this attack wasn’t to kill but to simply scare us into changing our way of life. In addition to taking off our shoes and loosing our duty free liquids, it looks like we’ll now be subject to inner thigh pat downs.  I fear the next terrorist will smuggle explosives on board internally leading to the ultimate in security humiliation – the full body cavity search.

While we may not be able to control the reasons why these people may want to kill or hurt us, we can control how we react. By limiting our responses to something more proportional to the threat (like that of peanuts and lightning strikes) we can reduce both the effectiveness and incentive of terrorist actions. To defeat terrorism, we must stop being terrified.

To rehash my plan, I think it is entirely possible to learn a language to a functionally fluent level in 2 months.  From my somewhat limited grip of linguistics and philosophy of language, I can see three major tasks ahead:

1. Rote learn the 500 most frequent words,
2. Learn the primary syntactic structures,
3. Learn some local colloquialisms and slang.

Time to get cracking…..

UPDATE: A frequency list of German words was pretty easy to find.  I’m currently in the process of separating these into word types which I’ll post later.

For those with even less understanding of quantum mechanics than I have, Wikipedia provides a nice introduction

Quantum indeterminacy is the apparent necessary incompleteness in the description of a physical system, that has become one of the characteristics of the standard description of quantum physics. Prior to quantum physics, it was thought that (a) a physical system had a determinate state which uniquely determined all the values of its measurable properties, and conversely (b) the values of its measurable properties uniquely determined the state. Albert Einstein may have been the first person to carefully point out the radical effect the new quantum physics would have on our notion of physical state.

Quantum indeterminacy can be quantitatively characterized by a probability distribution on the set of outcomes of measurements of an observable. The distribution is uniquely determined by the system state, and moreover quantum mechanics provides a recipe for calculating this probability distribution.

My issue with quantum indeterminacy stems from a failure to properly distinguish between metaphysical and epistemic indeterminacy.  Metaphysical indeterminacy is the claim that the external world (at the quantum level) is indeterminate whereas epistemic indeterminacy is the merely claim that it is our understanding of the external world that is indeterminate, not necessarily the world itself.  This is a significant distinction that the case of a coin flip and Schrodinger’s Cat highlight.

To say that when I flip a coin, the outcome is random and conforms to probabilistic behavour belies the reality that the outcome is causally determined.  It is not the case that the coin ‘randomly’ or indeterminately lands on heads or tails – the outcome is determined by the angle and velocity of the flip, air resistance, arc and length of fall etc.  My knowledge of the outcome may be indeterminate, but the outcome has a physical cause.

Likewise, the paradox of Schrodinger’s Cat is only paradoxical when metaphysical and epistemic indeterminacy are confused.  We don’t know whether the cat is alive or dead (or both alive and dead) until we open the box, but to claim that the cat is both alive and dead in reality seems, to me at least, clearly wrong.  Just because we can’t observe some causal state to explain quantum mechanics, doesn’t support the claim that indeterminacy exists in a metaphysical sense.  Absence of evidence is very different to evidence of absence.

One of the most common logical fallacies is asserting the consequent.  This is an argument with the form

If P then Q
Q
Therefore P

This is a logical fallacy because the conclusion does not necessarily follow from the premises – there could be many reasons for Q that don’t involve P.  Despite this fallacy being well known since Aristotle’s day, there is no end of management theorists out there writing case studies on successful firms or people by examining what they did and assuming this to be the cause of their success.

Good to Great by Jim Collins is a classic example of asserting the consequent.   To paraphrase 9 chapters:

We surveyed the market and identified 11 great performing companies.
Those 11 companies all showed 7 key characteristics.
Therefore those 7 characteristics are what made them great.

Right.  Ah, what about all the other companies with those characteristics that didn’t succeed? With millions of copies sold, I guess this is more proof that lack of a sound argument is no impediment to publishing success in the business/management genre.  Given that Fanny Mae and Circuit City were out of business within 7 years of the book being published, Collins’ definition of ‘great’ may have a pretty short half life.

Another favourite fallacious example of mine Stephen Covey’s Seven Habits of Highly Successful People.  Here, he distills the characteristics of successful people as to such gems as be proactive, think win/win and synergize.

All good things to do but are they really what separates the successful from the non-successful.  Are there ‘failures’ that exhibited these habits and are there successes that didn’t.  In order to develop a more accurate list of the habits that truly separate the successful from the failures, the haves and the have nots, I propose a the New Seven Habits of Highly Successful People:

1. Skiing
2. Driving sports cars
3. Polo
4. Wearing diamonds
5. Yachting
6. Shopping
7. Buying art

I guess the topic of causation will have to wait for another day.

One night mid season, Tina and I were at a BBQ with some local lifties at the top of the mountain.  It was quite a blast – drinking and dancing on ski hut roofs – until the trip home on a 30cm plastic mini-bob at midnight.  The afternoon had been quite warm and the snow was a nice spring corn so I thought it would be a breeze sledding the 1000m vertical down to the valley.  Unfortunately, by the time we left, the piste was a frozen solid sheet of ice and the mini-bob was uncontrollable.  Below is a clip of Hermann Maier strutting his stuff down the Kandahar.  He took 1:57 minutes.  We took 1:57 hours.

Luckily for us, the orange netting was still up from the World Cup the week before.  It came in very handy.  Even luckier, Tina is still talking to me.

My concern stems from a few key implicit assumptions that underpin processes like six sigma.

1. That there are adequate feedback mechanisms to highlight effectiveness (or lack there of).
2. That there are adequate feedback mechanisms to effectively encourage innovation.

Six sigma was designed for profit driven organisations.  A pre-existing element of such firms are relatively strong feedback systems for information (financial metrics) and reward (promotion and pay based on P&L performance).  That organisations and their staff want to innovate, and that they have the metrics to measure financial improvement, is a strong presupposition within quality/improvement frameworks.

Most Government departments I’ve encountered either lack these feedback systems or they are insufficient.  Many may have financial metrics in place, but rarely are these metrics embedded in the organisational culture and used to the same degree as in profit driven firms.  Importantly, assuming these organisations both want to improve or have the financial metrics available to improve is not a valid presupposition.  There are certainly many dedicated staff in Government but to claim they have the same vested interest in the financial performance of their department that private sector managers do is simply wrong.

So what can Government or non-profit organisations do?  Firstly, they need to acknowledge the assumptions in improvement frameworks and make them explicit.  Secondly, they need to develop a process of simulating these feedback mechanisms.  Financial and other performance metrics are relatively easy to produce.  Instilling a culture of financial and operational efficiency is another matter however.

For my part, while six sigma should be applicable to any industry or environment, I don’t see it being successful until the implicit assumptions that underpin it are made explicit.  I’d be very interested in seeing some empirical evidence on the success of profit vs non-profit implementations of six sigma.

I can’t see how probability theories can provide any justification for inductive reasoning.   Standard approaches to probability such as Bayesian Probability require the prior probability of a phenomenon to be known.  Clearly, this prior probability is impossible to deduce for anything other than artificial constructs such as games of chance, and as such, is of little use in science and the external world.  Put simply, how can we know the actual probability of something before we have experienced it?

Probability derived from observed frequency is equally problematic.  Frequency probability is calculated by dividing the number of observed events (n_x) by the number of trials (n_t) so that as the number of trials becomes ever larger, the expected probability approaches the real probability.  Thus:

P(x) = lim(n_t -> ∞) n_x / n_t

It becomes immediately apparent that frequency probability has significant limitations when P(x) is close to 0 or 1.  The expected probability will always lag the actual probability of a phenomenon, underestimating certainly when close to 0 and over estimating certainty when close to 1, which is precisely the domain where science is most interested.  The story of Russell’s Turkey provides a vivid example of the ineffectiveness of frequency probability calculations, as even after 364 observations, on Christmas Eve the expected probability that the turkey will be fed at 9 am the following morning is 1.

Perhaps a more fundamental flaw in justifications from probability based on the degree to which one could rationally believe a claim, and experience in general, is this.  The calculated probability or expected likelihood of an event is contingent upon the observer’s knowledge of the phenomenon, however the observer’s knowledge is independent of the underlying nature of the phenomenon.  There is a disjoint between expected and actual probabilities that cannot be determined a priori.  As Hume (EHU V.I) noted, the particular causes by which all natural operations are performed, never appear to the senses.  Because we cannot observe causes, only their effects, we have no way of knowing the nature of the phenomenon that causes those effects.

Time for a thought experiment.  Consider an example of an alien coin.  Unlike coins made by man, this one is controlled by a different natural force, so that its characteristics are either random, consistent, or drawn to equilibrium.  The characteristics are fixed and determined at the time of minting but are completely unobservable a priori.  After flipping the coin and landing 10 heads in a row (the urge to imprint faces on coins seems truly universal), it remains impossible to accurately estimate the probability of the next toss also being heads.  If the coin is random, then probability is independent and 0.5.  If the coin is consistent, then the probability of another head is 1, while if the coin is drawn to equilibrium (say, has a memory), the probability is 0.000488 (1 / 2¹¹).  As this example shows, inductive reasoning requires a uniformity of nature to be effective but that uniformity cannot be assumed and cannot be observed a priori.

So, can probability ever be useful?  Like induction, it seems to work most of time but can never be proved or be found conclusive before the fact, except for artificial games of chance.  Personally, I get very concerned when people start using probability based on historical data to ‘demonstrate’ how some phenomena (say the share market) will or wont behave in a certain way.