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1e82cd3 Better way of handling custom data stuff
frabcus authored
1 Ideas of things that could be done with Public Whip data, or similar.
2 I don't intend to do any of them, as they don't fit my goals - but they
3 might give you useful suggestions. There are probably a few political
4 science papers in here.
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6 Some similar things done with US voting data:
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9 Party politics
10 --------------
12 Table of most rebellious by party - so see most rebellious Con and LDem.
13 At the moment only Labour show up.
14 Table of highest attendance by party - similarly.
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15 Rankings on rebellion/attendance PER PARTY
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17 Compare attendance rates between parties, as they go in and out of
18 government over the years (use raw data "Extra Turnout" uses)
19 Compare rebellion rates between parties
21 Find out must rebellious divisions by party
22 e.g. find out what issues are fracturing the Tories
24 Statistics by party - e.g. attendence rate.
25 How rebellious a party it is. etc.
27 Proportion of abstentions within each party, may reveal times when MPs abstain in protest.
29 % of completely pliant MPs in each party, who always follow whip.
31 Do Co-op members ever vote against Labour as a group?
33 Academic analyses (of no short term practical political benefit)
34 -----------------
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36 Graph of how many MPs defect in each vote over time
37 Watch for loyalty going down after start of term, to lowest at midterm,
38 then up again
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40 Analyse if MPs who are "sir" vote differently in anyway
41 first check data integrity that title always has "Sir" for knights
42 Get data on gender etc. and analyse against that
44 Regional analysis. Scotland, NI, Wales, North v South. Urban v. Rural.
45 Area of land for constituency. This gives a "ruralness" measure.
46 Population of constituency.
47 Distance of constituency from London vs. attendance rate
49 Integrate parliamentary majority, and look for correlations with
50 rebelliousness? Majorities here:
52 (Should be no correlation, as reselection more important?)
53 Plot majority as a colour on the cluster diagram
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54 dONE - no correlation. see website/custom/majority-rebellions.png
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56 First term MPs vs. old warhorses. More rebellious? Less attentive?
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2546380 Postcode search
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58 Find people who have telled the most times
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60 Cluster distractions (geek fun, but pointless)
61 --------------------
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63 Make clustering cope with tellaye/tellno
64 Make cluster stuff store NUMBER OF VOTES both voted in for extra possible friends info
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66 Chris Lighthead: "I've now written some code to estimate which of the
67 eigenvectors are significant. The basic idea is that we generate
68 synthetic data using the marginal distributions for each statements --
69 that is, like the data which would have been produced by the same number
70 of respondents as have completed the real survey, but as if their
71 answers to any one question were unrelated to all the others; and having
72 done that, we perform the principal components analysis on the synthetic
73 data. The idea here is that we can compare the eigenvalues from the
74 synthetic data to the eigenvalues from the real data. If the real
75 eigenvalue is significantly larger than the one from the synthetic data,
76 it likely represents real variation in the data; otherwise, random
77 variation." - we could do this with MP clustering.
79 Improve clustering distance algorithm
80 See J Vaughan suggestions
82 Colour dots in cluster diagram by how many times they have voted.
83 Bright colours for more relevant the data - i.e. how many intersections
84 with other's votes there are.
86 Play with stuff in vector search article
88 In particular PDL for speeding up octave algebra stuff
90 > Idea 2. Darren suggested that the reason Tony Blair is an outlier
91 > in the java app is coz he only turns up to votes he thinks are
92 > going to be controversial, hence ones that people are probably
93 > going to vote against him.
94 Find a metric to see if this is the case.
96 Make cluster diagram for just divisions relating to one issue. Or
97 for one person's interested issues. Plot point on cluster diagram for
98 issues themselves.
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99 [I've tried this, with not that useful results - Francis:
100 - I've made a cluster diagram with just the Iraq votes in.
101 Unfortunately it isn't really revealing, kind of curious, but I'm not
102 sure how useful it is in the media. Maybe you have suggestions
103 otherwise! Find a static screenshot attached.
105 Anti-war on the left, pro-war on the right. Colours represent
106 political party. Unfortunately, lots of the dots represent dozens of
107 MPs when they all voted the same, so the distribution is much denser
108 to to the right than it at first appears. It's interesting that Con
109 and Lab still separate out top to bottom... We almost end up with four
110 corners.
112 Top-left: Anti-war, anti-government
113 Top-right: Pro-war, anti-government
114 Bottom-left: Anti-war, pro-government
115 Bottom-right: Pro-war, pro-government
117 However, this doesn't really tell us anything we didn't already know. ]
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119 EDM analysis with MDS:
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122 Written Answers
123 ---------------
125 Here's a couple of ideas: a section called "answers that are in the Library".
127 Also, if we find enough funny business, what about, random question of
128 the day? People could subscribe to this, and this would get them involved.
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131 Miscellaneous
132 -------------
134 Create classification tree so it offers some division questions for you
135 to pick from, and tells you your party. As does here for EDMs:
138 Find "Motion made, and Question proposed," and "Question put and agreed
139 to." when there was no division. Record these "virtual divisions" as
140 divisions, as they are really, just they were totally uncontested for
141 whatever reason. Count them up and see where and how many there are,
142 whether there are more near bedtime etc.
144 What can we learn from the information that aye/no comes first, and
145 from the information as to whether government or not government is
146 aye or no?
148 Measure lobbying power behind each issue (expenditure by interested
149 parties). Again, correlate to time spent on it.
151 Value of the vote. What is the monetary expenditure cost of agreeing
152 the motion? Graph against time spent discussing, and see how silly the
153 correlation is.
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155 Measure a sudden drop in attendance rate - so you could see that the MP
156 used to vote a certain % of the time and now doesn't. This will
157 detect illness/injury/busy for some other reason.
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