Podnocker rebuild and redesign

This post has been coming for a while—a commented photographic detail of my boat reconstruction project, that I first conceived of and wrote about just over a year ago.  Read that post first!  What started out as a project to “repair and repaint” essentially became a project to rebuild the boat from its guts.  The project took about a month from the time the motor came off until it was seaworthy again—though even then it was still in rough shape, without carpeting, electrical systems, or a completed paint job.  Finally finishing it took another couple of months in the evenings and weekends of last fall.

Before I go through all the details, here are the before and after shots (in the exact same spot, almost three years apart):

I’ve split this post up into three parts:

Deconstruction – rotten crap out

Reconstruction – new materials in

Redesign – repainting and redecorating

New economic thinking

In applying for a workshop taking place later this year, I was asked to write up to 250 words on what I think “new economic thinking” means and why it is important.  This is what I wrote (and believe):

 

The pessimist in me too often sees Economics as a discipline whose objective is to maximize understanding of socio-economic issues subject to a rigid set of mathematical tools. We’re often a discipline unaware of the limitations we impose on ourselves: as a professor of mine once observed, when the real world doesn’t agree with our models, economists tend to question the real world rather than our tools.

New economic thinking should be about being more aware of our limitations, and more willing to accept new approaches, untying ourselves from older, limiting ones. Those new approaches can come from other disciplines–for example, modelling the behaviour of our agents on research from psychology, or allowing for emergent behaviour from complexity that computational economists would have us explore through agent-based models. We need to recognize that equilibrium is only one of many possible states of the world, and that what happens away from equilibrium is no less important than what happens at equilibrium.

New economic thinking must be cognisant of and open to these new approaches. We need to accept at least the novelty, if not the results, of bold new approaches to exploring the behaviour of the world around us in the hope that at least some of those approaches give us a revolutionary leap in our ability to analyse social behaviour. Fundamentally, new economic thinking needs to be about new thinking for old problems rather than the easier but limited pursuit of new tweaks to old models.

Agent-based Computational Economics

Leigh Tesfatsion concludes her paper (Agent-based Computational Economics: A constructive approach to Economic Theory, 2006, in the Handbook of Computational Economics) beautifully summing up how I feel about the subject and approach:

As a professor of mathematics (as well as economics), I appreciate the beauty of classical mathematics. However, constructive mathematics is also beautiful and, in my opinion, the right kind of mathematics for economists and other social scientists. Constructive mathematics differs from classical mathematics in its strict interpretation of the phrase “there exists” to mean “one can construct.” Constructive proofs are algorithms that can, in principle, be recast as computer programs. To master a general programming language is to acquire a form of mathematical skill every bit as aesthetically pleasing, powerful, and practical as the differential calculus. Indeed, for economic purposes, computer programming is in some ways more powerful in that it facilitates the modeling of complex interactive processes involving kinks, jumps, and other forms of discreteness imposed or induced by empirical constraints. Consequently, programming frees us to adapt the tool to the problem rather than the problem to the tool. Every graduate economics program should incorporate general programming language requirements. It is time.

(Emphasis mine).  This is what I’m trying to do, and trying to encourage others to at least accept, but it seems an uphill battle.

Kingston bike theft

I had my first direct experience with Kingston’s legendary bike theft this morning, when I went to unlock my bike to ride to my office.  The lock was a mess: the plastic sheath around the lock was in tatters, and there were numerous scrapes and scratches to the lock, and my bike around where the lock was attached.

Despite a bit of cosmetic damage, the thief entirely failed to actually steal anything, making me thankful that I decided to spend money on a quality lock.  Just for the record, in case anyone needs a bike lock recommendation, I’m very happy with my Bikeguard Rocklock 1500.

I only wish the would-be thief had been a little smarter and not bothered at all.  But then again, if the would-be thief had been a little smarter, he probably wouldn’t have decided to become a thief at all.

Edit: image of the mess left behind:

IMG_20130730_091918

John Orr Tower ­— Queen’s Community Housing

To potential new tenants in John Orr Tower (or An Clachan, or other “core” Community Housing properties), I offer this advice: keep looking.  You can find a better apartment at a better location at a lower price with a landlord who, unlike Queen’s Community Housing, won’t be able to take advantage of you when it comes time to renew your lease.

About John Orr Tower

I’ve been living in John Orr Tower, operated by Queen’s Community Housing, for 2 years, 10 months, and 23 days, as of this post.  I’ve served over that period as the building representative for Community Housing, and as such I have some notion of the planning and internal decisions made behind the management of John Orr Tower (and other Community Housing properties).  That position carries no actual weight towards any decision—meetings are entirely a one-way source of information from Community Housing to representatives.

Up until about a year ago, I was relatively happy living in the building; I have a decent view of Lake Ontario and Wolfe Island, there’s a bus every 15 minutes to main campus, the apartment isn’t too expensive, and the walls are thick so I’m never bothered by neighbours.

But during my time here things started changing, in part due to larger Queen’s fiscal problems.  Community Housing stopped treating its properties as a benefit to students, and started trying to extract as much money as possible from students, while being as cheap as possible on building repairs and upgrades, lying to tenants (and myself, the “representative”) about changes, and using its status as a university to exploit legal loopholes regarding rent termination and increases.

Continue reading John Orr Tower ­— Queen’s Community Housing

Cat tree

In August, I’ll be moving into a new apartment, with a larger bedroom and two roommates—plus Nibbler and Kallie.  The cat tree I have for them (the top half is shown here, brand new) is 2 years old, and not in very good shape: the covering on the top perch has disintegrated, the sisal rope at the base (used often as a scratching post) is coming off, one of the lower perches is broken (my fault).  Closer inspection has revealed just how cheaply it was made: particle board, cardboard tubes, poor quality covering.

Thus, considering the larger space they (and I) will have in August, I’ve started thinking about building a replacement (possibly for August, maybe a little later).  I’ll update this post as I come up with new ideas, perhaps with some pictures as the thing actually takes shape.

Core ideas:

  • TWO top perches.  Both cats think the top perch is the best place to be, and once one cat gets onto the top, the other is entirely out of luck: attempts to fight up to the top fail.  The two perches need to be sufficiently far apart that one cat cannot monopolize both.
  • Raised edges on the top perches.  Kallie, in particular, likes to sleep on the top, but I think it’s a little difficult for her to be really comfortable there because of the risk of falling off.  Nibbler might like to sleep there, but is just too big to do anything than sit there, awake.
  • A large, heavy base.  Once in a while some rambunctious activity results in the current cat tree toppling, crashing into either a bookcase, my dresser, or my laundry basket.  The current base is too small, and too light.
  • Soft, but tough carpeting.  It needs to be easy to clean/vacuum, and I don’t want it to turn into a disintegrating mess after a year or two.

Optional ideas:

  • Box at the bottom.  The current cat tree has a raised box, with a hole on top and hole at the corner (so the cat can go through it).  It’s too small for an adult cat, though; Kallie sometimes dives in after a toy, but it’s too small even for her to lie comfortably in; forget about Nibbler.  Both cats (Nibbler especially) enjoy their “cat tube” (see below), and I think would similarly enjoy a proper-sized enclosed space.  Having openings at two ends (or maybe top and side, like the current one?) would be good as well.
  • Adjustable perch heights.  This depends on how, exactly, I go about attaching it, but is something to keep in mind.

 

More ideas to come.

Economic modelling of behaviour

One of the big problems faced in economics, particularly in macroeconomics, is the bugbear of uncertainty. Actually, that’s not right: it’s one of the problems we try *not* to face. Typically, at most, we handle uncertainty by deciding upon a set of events, and assigning a probability to each, then assume that an agent in our model knows the events and probabilities of each.

Prima facie, that seems wrong: typically real people don’t know the probability of an event. The defence of the assumption, however, goes something like this: people aren’t stupid, therefore as they see reality unfolding and see uncertainty resolving itself, they will adjust their behaviour. Since we’re often modelling long-term repetitions of the same set of events, even if people initially guess the wrong probabilities, by observing the events that occur, they will update their beliefs on the probabilities, converging to the true probabilities.

This seems wrong to me, still: casual observation yields examples every day where people make the same mistake, again and again, and don’t update their beliefs–or update them wrongly. For example, flip a coin 100 times.  Straight, non-human-interpreted probability says that there is a better-than-even chance of seeing a string of 7 of the same side of the coin in a row somewhere in that 100 flip sequence, and more than a 10% chance of seeing 13 in a row. Or take a pair of dice rolled 100 times: there’s a 15 percent chance that the same total will be rolled 4 times in a row somewhere in the 100 roll sequence. But we humans aren’t very good at dealing with probabilities: when we see 7 heads in a row, we start thinking the coin must be biased, or the dice must be loaded.

Continue reading Economic modelling of behaviour