2021 review – statistics

Below are some statistics about the 12th year of Equality-by-Lot. Comparable numbers for last year can be found here.

2021 Page views Posts Comments
Jan 2,684 13 182
Feb 3,105 15 117
Mar 3,253 11 131
Apr 3,096 9 118
May 3,303 14 34
June 2,806 11 70
July 2,408 7 76
Aug 2,506 6 41
Sept 2,314 11 93
Oct 2,400 8 102
Nov 2,388 10 136
Dec (to 21st) 2,133 10 92
Total 32,396 125 1,192

Note that page views do not include visits by logged-in contributors – the wordpress system does not count those visits.

Posts were made by 20 authors during 2021. (There were, of course, many other authors quoted and linked to.)

This blog currently has 152 email followers, 334 WordPress followers and 499 Twitter followers (@Klerotarian).

Searching for “distribution by lot” (with quotes) using Google returns Equality-by-Lot as the 2nd result (out of “about 330,000 results”). Continuing the demotion trend which has begun last year, Equality-by-Lot is now on the 10th page of results when searching for “sortition” using the Google search engine (out of “about 285,000 results”). This demotion may explain the significant decline in the total number of views in 2021 relative to 2020.

Happy holidays and a happy new year to Equality-by-Lot readers, commenters and posters. Keep up the good fight for democracy!

3 Responses

  1. >Continuing the demotion trend which has begun last year, Equality-by-Lot is now on the 10th page of results when searching for “sortition” using the Google search engine.

    That’s disappointing (especially in light of the change of subtitle). Any idea why that might be?

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  2. One can only speculate what made Google’s algorithm decide that when someone searches for “sortition” then they are more likely to be interested in, say, the paper “Neutralizing Self-Selection Bias in Sampling for Sortition” by Bailey Flanigan et al., published in 2020 in the journal “Advances in Neural Information Processing Systems”, rather than in this blog.

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  3. Perhaps if we all make a New Year’s Resolution to be civil to each other then new participants will not be put off (although the direct impact of this on the Google algorithm will be small), otherwise there is a risk we will be dismissed as a fissiparous cabal (aka pack of ferrets fighting in a sack). I repeat my suggestion to Terry that we should focus more on the things we all (or most) agree on. But thanks to Yoram for drawing our attention to what looks like a very paper on Neutralizing Self-Selection Bias in Sampling for Sortition:

    Sortition is a political system in which decisions are made by panels of randomly selected citizens. The process for selecting a sortition panel is traditionally thought of as uniform sampling without replacement, which has strong fairness properties. In practice, however, sampling without replacement is not possible since only a fraction of agents is willing to participate in a panel when invited, and different demographic groups participate at different rates. In order to still produce panels whose composition resembles that of the population, we develop a sampling algorithm that restores close-to-equal representation probabilities for all agents while satisfying meaningful demographic quotas. As part of its input, our algorithm requires probabilities indicating how likely each volunteer in the pool was to participate. Since these participation probabilities are not directly observable, we show how to learn them, and demonstrate our approach using data on a real sortition panel combined with information on the general population in the form of publicly available survey data.

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