Predicting the 2015 Canadian election

The Canadian general election will be held on 19 October. The most basic prediction method uses the full district (“riding”) vote information from the last election (in 2011), the current poll estimate for national level support for each party, and a model of changes in district votes. There are two main models used in predicting elections under First Past the Post (single-winner plurality in districts), namely Uniform (additive) Swing and Proportional (multiplicative) Swing.

Based on the aggregate poll at signal.thestar.com, these two models predict the following point estimates for the seat distributions (after scaling up to account for the increase in parliament size since 2011):

Multiplicative: CON 133 NDP 71 LIB 125 BQ 7 GRE 1
Additive: CON 145 NDP 85 LIB 101 BQ 6 GRE 1

NDP have lost a lot of support in recent weeks, but it still looks as though no party will have an absolute majority and CON will be the largest party.

UPDATE 19 October (NZ time): using the latest poll estimate the models now give:

Multiplicative: CON 131 NDP 72 LIB 128 BQ 3 GRE 1
Additive: CON 137 NDP 86 LIB 109 BQ 5 GRE 1

ThreeHundredEight.com predict: CON 120, NDP 71, LIB 141, BQ 5, GRE 1
Toronto Star predict: CONS 124, NDP 71, LIB 140, BQ 2, GRE 1

Let’s see the results tomorrow.

Official Information Act requests in the style of Tim Gowers

Update: information from Victoria University of Wellington received.

Inspired by Gowers’ monumental effort to find out how much commercial publishers are charging universities for journal access, I have sent Official Information Act requests to New Zealand universities. It seems that in NZ (unlike UK) there is no right of internal appeal against a decision to decline to give information, and the next official step is to go to the Ombudsman, whose office is, I am told, overworked.

Here is what I have found out so far. I sent similar requests to several places, but made minor changes out of boredom and interest to see whether a different result would be obtained. As expected, the initial replies have not been very helpful. The next step is presumably to contact these institutions informally and see whether any rewording of the request could be more effective. Beyond that, all I can see is a long wait for the Ombudsman.

The replies (edited down to the essentials) so far are below. It doesn’t seem that there has been as much coordination with Elsevier as Tim suspected in the UK situation. Different excuses are given, which may make at least complaints to the Ombudsman more likely to succeed.

A note on overall journal subscription costs: this information for Australian and NZ universities can be obtained at http://statistics.caul.edu.au/inst_data.php According to this, for example, in 2013 University of Otago spent over AU$8.4M in serial subscriptions, just under AU$1.9M in non-serials, and a little over AU$9.0M in salaries. So journal subscriptions make up a very large fraction of their budget.

University of Auckland

The University currently pays Taylor/Francis USD 413,715 + AUD 20,292 and Wiley USD 891,067.

Making information about what we currently pay Elsevier and Springer for journal access available would be likely to unreasonably prejudice the commercial position of the University. Withholding this information is necessary to enable the University, without prejudice or disadvantage, to carry on negotiations with these publishers. Accordingly, the information requested is withheld under s 9(2)(b)(ii) and s 9(2)(j) of the Official Information Act.

AUT

AUT has a contractual arrangement with Elsevier. For this reason we have reached the decision that it is necessary to withhold the information in accordance with section 18 (a) Official Information Act 1982 and pursuant to section 9(2)(i) to enable the University to carry on, without prejudice or disadvantage, commercial activities and section 9(2)(j) to enable the University to carry on, without prejudice or disadvantage, negotiations.

University of Waikato

The University and Elsevier have a confidentiality agreement regarding the financial and commercial terms of their contract. Your request is therefore refused under Section 9(2)(b)(ii) of the Official Information Act 1982 on the grounds that making the information available would be likely unreasonably to prejudice the commercial position of Elsevier.

Massey University

You have requested details of Massey University’s expenditure annually for access to Elsevier journals. You have specifically requested the total annual fee, split into three components. You have also requested the annual total budget for journal access for all publishers.

Massey University advises that the access to Elsevier electronic journals is subject to a confidential legal agreement. Accordingly, Massey University declines to release the information requested under section 2 (b) (ii)  of the Official Information Act 1982 – which protects the commercial position of those who are subject to the enquiry e.g. Elsevier and Massey, and 2 (ba) which provides for protection of information which is subject to an obligation of confidence.

Victoria University of Wellington

In 2013 they paid Taylor & Francis $484000 and Wiley $542856.  This is for (T&F) Core Journal Collection, Social Science Journals, Science and Technology Journals, CRCnetBASE products; (Wiley) Wiley e-journal package, Current Protocol Online. They also said

The details for Elsevier and Springer are withheld under Section 9(2)(j) of the Official Information Act 1982, on the basis that withholding this information is necessary to prevent prejudice or disadvantage to the ability of Victoria to carry on negotiations with these providers.

 

University of Canterbury

The University can release to you the second part of your request. The total Library information resources budget for 2014 is $5.9M. … A reasonable estimate of ongoing journal purchases would be $4.6M. ….

The University is withholding the first part of your request – the total annual fee for Elsevier journals – under Section 9(2)(ba) of the Official Information Act on the basis that the information is subject to an obligation of confidence created by a confidentiality clause at 7.8 of the agreement we hold with Elsevier.

The University also withholds this information under Section 9(2)(b)(ii) on the basis that making the information available would be likely unreasonably to prejudice  Elsevier’s commercial position where they have negotiated specific terms with us.

Lincoln University

I have not made a formal request. An informal one to the library resulted in:

I am afraid that Lincoln University is unable to provide you with this information. Most licence agreements prevent us from disclosing this information. I am sorry I am unable to be more helpful.

University of Otago

In 2013 the University of Otago’s budget for print journals and eresources (this includes all e-continuations, databases, journals, streaming video, ebook collections etc  – with ongoing fee, not just journals) was NZD $9,031,438.

The amount spent annually for access to Elsevier journals is withheld under sections 9(2)(i) and 9(2)(j) of the Official Information Act.  The reasons being commercial sensitivity and prejudice to commercial negotiations.

 

University ranking analysis

Warren Smart has analysed the recent performance of Australian and NZ universities in the three most prominent international university rankings (ARWU, QS, THE). There is a lot of detail there, not all of it depressing. It is going to be hard for NZ to keep being satisfied with “punching above its weight” in the face of lower income per student than just about anywhere we want to compare ourselves with. As a country, we may indeed have too many universities for them all to rank well internationally. But the good thing about NZ is that change can happen rapidly. So, please consider the policies of all parties in the areas of tertiary education, research, innovation, etc when voting in the general election on 20 September 2014.

Edit: the situation with NZ university rankings has been discussed quite widely recently. Some links:

Paradoxes of runoff voting

The New Zealand Labour party will soon have an election for leader of its Parliamentary caucus. The voting system is a weighted form of instant runoff using the single seat version of Hare’s method (instant runoff/IRV/alternative vote). IRV works as follows. Each voter submits a full preference order of the candidates (I am not sure what happens if a voter doesn’t rank all candidates but presumably the method can still work). In each round, the voter with smallest number of first preferences (the plurality loser) is eliminated, and the candidate removed from the preference orders, keeping the order of the other candidates the same. If there is a tie for the plurality loser in a round, this must be broken somehow.

The NZLP variant differs from the above only in that not all voters have the same weight. In fact, the caucus (34 members) has a total weight of 40%, the party members (tens of thousands, presumably) have total weight 40%, and the 6 affiliated trade unions have total weight 20%, the weight being proportional to their size. It is not completely clear to me how the unions vote, but it seems that most of them will give all their weight to a single preference order, decided by union leaders with some level of consultation with members. Thus in effect there are 34 voters each with weight 20/17, 6 with total weight 20, and the rest of the weight (total 40) is distributed equally among tens of thousands of voters. Note that the total weight of the unions is half the total weight of the caucus, which equals the total weight of the individual members.

IRV is known to be susceptible to several paradoxes. Of course essentially all voting rules are, but the particular ones for IRV include the participation paradoxes which have always seemed to me to be particularly bad. It is possible, for example, for a candidate to win when some of his supporters fail to vote, but lose when they come out to vote for him, without any change in other voters’ behaviour (Positive Participation Paradox). This can’t happen with three candidates, which is the situation we are interested in (we denote the candidate C, J, R). But the Negative Participation Paradox can occur: a losing candidate becomes a winner when new voters ranking him last turn out to vote.

The particular election is interesting because there is no clear front-runner and the three groups of voters apparently have quite different opinions. Recent polling suggests that the unions mostly will vote CJR. In the caucus, more than half have R as first choice, and many apparently have C as last. Less information is available about the party members but it seems likely that C has most first preferences, followed by J and R.

The following scenario on preference orders is consistent with this data: RCJ 25%, RJC 7%, CRJ 10%, CJR 30%, JRC 20%, JCR 8%. In this case, J is eliminated in the first round and R wins over C in the final round by 52% to 48%. Suppose now that instead of abstaining, enough previously unmotivated voters decide to vote JRC (perhaps because of positive media coverage for J and a deep dislike of C). Here “enough” means “more than 4% of the total turnout before they changed their minds, but not more than 30%”. Then R is eliminated in the first round, and C wins easily over J. So by trying to support J and signal displeasure with C, these extra voters help to achieve a worse outcome than if they had stayed at home.

The result of the election will be announced within a week, and I may perhaps say more then.

Reinventing Discovery

I highly recommend the book (published in 2011, but I have only just read it – it’s hard to be on the cutting edge) Reinventing Discovery by Michael Nielsen. He “wrote this book with the goal of lighting an almighty fire under the scientific community”. His overview of Open Science, of which Open Access to publications is just one component, is very compelling and optimistic, without losing sight of difficulties.

Submission to the Electoral Commission Review of MMP

I missed the first deadline for proposals for submissions to the review, but now that the Proposals Paper has been released, it has focused attention on a smaller number of issues. With Michael Fowlie (current COMPSCI 380 project student) I have made a submission based on simulations of what we hope are “realistic” elections. We find that the party vote threshold should be lower than the 4% recommended by the commission. I have been told by the EC that our submission will be an appendix to their report due out on 31 October. It will be interesting to see a) their recommendations b) whether they lead to any actual change.

Addendum: our submission appears as Appendix D in the commission’s final report to Parliament. They went with the 4% recommendation in the end.

Departmental happenings

My department has started a blog aimed at increasing public understanding of computer science and raising our profile. The NZ secondary school curriculum and the news media clearly conflate CS (computer science) with IT (information technology), and this must be resisted.

The department’s annual public lecture series is coming up. Detail:

The Gibbons Lectures 2012: The Turing Legacy

The Department of Computer Science is delighted to announce the 2012 Gibbons Lectures. The lectures describe developments in research in Computer Science and are aimed at a general but technical audience – to Computer Science students at all levels, to IT practitioners in other departments and outside the University. The lecture series is memory of Associate Professor Peter Gibbons, who sadly passed away early in 2008.

2012 Synopsis:
Alan Matheson Turing was born in 1912. It is now widely accepted that he was one of the most important founders of both theoretical and practical computing, although he died in 1954 just when the field of computing was getting underway. Many of his contributions were not widely recognized at first, but this year, the hundredth anniversary of his birth, he is being celebrated by a series of events organized world-wide. We are joining the festivities by devoting this year’s Gibbons lectures to Turing and his influence.

Turing’s work was the basis for many areas of computing research and development that are still on-going. We have in New Zealand and our Department researchers who are experts in some of these areas and also experts in Turing and his achievements. The four Gibbons lectures this year will involve University of Auckland speakers discussing four topics in the rough order of Turing’s involvement during his lifetime.

Presented in association with the New Zealand Computer Society.

Schedule of lectures:
Thursday 26 April: Alan Turing and the Unsolvable Problem: To Halt or Not to Halt – That is the Question (Professor Cristian Calude)
Thursday 3 May: NOTE: This lecture was recorded in Nov 2011 and will be webcast only, at http://www.cs.auckland.ac.nz/our_department/Gibbons_Lectures/
Alan Turing and the Secret Cyphers: Breaking the German Codes at Bletchley Park (Professor Jack Copeland)
Thursday 10 May: Alan Turing and the Computing Engine: Turing’s achievements in practical computing (Professor Brian Carpenter and Professor Bob Doran)
Thursday 17 May: Alan Turing and the Artificial Brain: The Development of Artificial Intelligence (Associate Professor Ian Watson)

Where: University of Auckland Conference Centre, 22 Symonds St, Building/room 423-342
When: 5.30pm for refreshments, prior to a 6.00pm start.
Please RSVP to robyn@cs.auckland.ac.nz for catering purposes.

Further information and abstracts are available on the Gibbons Lectures webpage at www.cs.auckland.ac.nz/our_department/Gibbons_Lectures/
Video streaming will be available via the webpage

2011 referendum simulator: experience so far

Several months ago I realized that the 2011 referendum in NZ on the voting system for parliamentary elections was coming soon. Geoff Pritchard and I developed a simulator with the aim of enabling voters to understand the consequences of a change to another system. In order to do this in a way that is useful to the non-expert, some simplifying assumptions must be made. We had substantial media coverage and some criticism.

Initial surprises:

  • How few people bothered to read the detailed FAQ before criticizing.
  • How many people thought that the simulator was trying to “back-cast” historical elections, and were certain that our results were unrealistic, without giving any evidence.
  • How much the criticisms, even unfounded ones, helped to clarify my understanding of what we had actually done, and suggested further research.
  • How short the attention span of internet visitors is.

In particular I want to respond to comments by David Farrar on his well-known site Kiwiblog. The relevant extract:

Now in 2002 National actually won 21 electorate seats out of 69 or 70. So this model is saying if there were 50 extra electorate seats, National would win 11 fewer seats!!

Why? Because they have come up with a formula based on the last 50 years or so of FPP elections, which they applied to the party vote figures for 2002. They ignored the actual electorate vote. It is a classic academic approach.

The more pragmatic approach, which is what others have done, is to say well if National won 21 electorate seats in 2002 out of 70, then if there 120 seats, their estimated number of seats would be 21*120/70, which is 36 seats.

In fact we did not look at any of the historical FPP elections The “formula” is based completely on the MMP party vote from the 2008 election (so yes, we did ignore the electorate vote, for what we think are good reasons).

However this got me thinking about how we might try to validate our assumptions. One way which I don’t (yet) claim is rigorous, but makes at least as much sense as the above, is to apply the simulator (the FPP part) to the historical FPP elections, and scale the 120 seats down to whatever it was historically (80 for many years, then increasing over time). The results surprised me greatly, as they are much better than expected, and this cries out for explanation (“further research”, always good for academics). Here they are. Note that these simulator results explicitly do not use any historical data, seat boundaries and parties have changed, etc.

1969: Real result was Nat 45 Lab 39; simulator scaled was Nat 46.9, Lab 37.1
1972: Real was Nat 55 Lab 32; simulator scaled was Nat 54.4, Lab 31.6
1975: Real was Nat 55 Lab 32; simulator scaled was Nat 55.1, Lab 31.9
1978: Real was Nat 51  Lab 40 SoCred 1; simulator scaled was Nat  47.5, Lab 44.5.
1981: Real was Nat 47 Lab 43 SoCred 2; simulator scaled was Nat 48.3, Lab 43.7
1984: Real was Nat 37 Lab 56 SoCred 2; simulator scaled was Nat 37 Lab 58.
1987: Real was Lab 57, Nat 40; simulator scaled was Lab 50.2, Nat 46.8
1990: Real was  Nat 67, Lab 29, NewLab 1; simulator scaled was Nat 71, Lab 26
1993: Real was Nat 50, Lab 45,  NZF 2, Alliance 2; simulator scaled was Nat 53.6, Lab 45.4