https://en.wikipedia.org/w/index.php?action=history&feed=atom&title=Wikipedia%3AReducing_consensus_to_an_algorithmWikipedia:Reducing consensus to an algorithm - Revision history2025-06-25T09:08:09ZRevision history for this page on the wikiMediaWiki 1.45.0-wmf.6https://en.wikipedia.org/w/index.php?title=Wikipedia:Reducing_consensus_to_an_algorithm&diff=1265101283&oldid=prevSMcCandlish: ce2024-12-25T03:00:19Z<p>ce</p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 03:00, 25 December 2024</td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>In plain English: Each source is assigned a contextual value, a combination of relevance to supporting the argument and reliability (reputability) of the source. These values are added together, then divided by number of sources presented, to produce an average. This step accounts for an increasing number of sources in support of the argument actually making the argument stronger, by slightly reducing the amount by which the relevance-and-reliability total is divided (in this model, for every ten sources you get a 1/10 bonus to argument credibility).</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>In plain English: Each source is assigned a contextual value, a combination of relevance to supporting the argument and reliability (reputability) of the source. These values are added together, then divided by number of sources presented, to produce an average. This step accounts for an increasing number of sources in support of the argument actually making the argument stronger, by slightly reducing the amount by which the relevance-and-reliability total is divided (in this model, for every ten sources you get a 1/10 bonus to argument credibility).</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>This is just a {{lang|de|[[Gedankenexperiment]]}}, since we have no objective way to assign numeric S and R values. Still, this {{em|does <del style="font-weight: bold; text-decoration: none;">seems</del> to fairly accurately model how we settle content disputes generally}}, if you reduce the process to statistical outcomes.</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>This is just a {{lang|de|[[Gedankenexperiment]]}}, since we have no objective way to assign numeric S and R values. Still, this {{em|does <ins style="font-weight: bold; text-decoration: none;">seem</ins> to fairly accurately model how we settle content disputes generally}}, if you reduce the process to statistical outcomes.</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>The more {{em|and}} better your sources are, the more your view will be accepted by consensus, all other things being equal. (Once in a while they are not equal, e.g. when a political or other [[WP:FACTION|faction]] has seized control of an article for the nonce and simply rejects ideas they don't like regardless of the evidence, until a [[WP:Noticeboard|noticeboard]] steps in and undoes the [[WP:Ownership of content|would-be ownership]] of the page.)</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>The more {{em|and}} better your sources are, the more your view will be accepted by consensus, all other things being equal. (Once in a while they are not equal, e.g. when a <ins style="font-weight: bold; text-decoration: none;">socio-</ins>political or other [[WP:FACTION|faction]] has seized control of an article for the nonce and simply rejects ideas they don't like regardless of the evidence, until a [[WP:Noticeboard|noticeboard]] steps in and undoes the [[WP:Ownership of content|would-be ownership]] of the page.)</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Given a non-staggering sample size of sources, the model even accurately captures the negative effect on A (credibility) when trying to rely on any obviously terrible sources even if other sources are high-end. Every source that does not have an R value close to 1 will drag down the average (much like how a failing grade on one exam or paper out of 10 in a class will significantly lower your overall grade even if you got straight ''A''s on all the rest of them).</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Given a non-staggering sample size of sources, the model even accurately captures the negative effect on A (credibility) when trying to rely on any obviously terrible sources even if other sources are high-end. Every source that does not have an R value close to 1 will drag down the average (much like how a failing grade on one exam or paper out of 10 in a class will significantly lower your overall grade even if you got straight ''A''s on all the rest of them).</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>It's not quite a perfect model, since it doesn't account for the fact that citing 100+ really terrible sources for a [[Wikipedia:Fringe theories|nonsense position]] ("[[Bigfoot]] is real", etc.) just makes you look crazy; the factoring of the effect of the number of sources is too simplistic.</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>It's not quite a perfect model, since it doesn't account for the fact that citing 100+ really terrible sources for a [[Wikipedia:Fringe theories|nonsense position]] ("[[Bigfoot]] is real", etc.) just makes you look crazy; the factoring of the effect of the number of sources is too simplistic<ins style="font-weight: bold; text-decoration: none;">. A better algorithm would apply a subtle modifier such that the positive effect of multiple good sources or negative effect of multiple bad sources progressively compounded</ins>.</div></td>
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</table>SMcCandlishhttps://en.wikipedia.org/w/index.php?title=Wikipedia:Reducing_consensus_to_an_algorithm&diff=1064149038&oldid=prevEthanGaming7640: Cleaned up using AutoEd2022-01-06T20:58:45Z<p>Cleaned up using <a href="/wiki/Wikipedia:AutoEd" title="Wikipedia:AutoEd">AutoEd</a></p>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* A = argument strength/credibility</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* A = argument strength/credibility</div></td>
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</table>EthanGaming7640https://en.wikipedia.org/w/index.php?title=Wikipedia:Reducing_consensus_to_an_algorithm&diff=908123241&oldid=prevOnBeyondZebrax: addpic2019-07-27T16:12:29Z<p>addpic</p>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>{{Nutshell|While consensus formation on Wikipedia cannot {{em|literally}} be reduced to a mathematical function, the likelihood of success of a proposition in a content dispute is actually fairly simple to predict with a model.}}</div></td>
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<td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><br /></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>One might think at first that a general model of [[Wikipedia:Consensus|Wikipedia consensus]] formation would look something like:</div></td>
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<td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>One might think at first that a general model of [[Wikipedia:Consensus|Wikipedia consensus]] formation would look something like:</div></td>
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</table>OnBeyondZebraxhttps://en.wikipedia.org/w/index.php?title=Wikipedia:Reducing_consensus_to_an_algorithm&diff=905909471&oldid=prevFayenatic london: update category, see Wikipedia:Categories for discussion/Log/2019 May 7 (via WP:JWB)2019-07-12T08:34:27Z<p>update category, see <a href="/wiki/Wikipedia:Categories_for_discussion/Log/2019_May_7" title="Wikipedia:Categories for discussion/Log/2019 May 7">Wikipedia:Categories for discussion/Log/2019 May 7</a> (via <a href="/wiki/Wikipedia:JWB" class="mw-redirect" title="Wikipedia:JWB">WP:JWB</a>)</p>
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</table>Fayenatic londonhttps://en.wikipedia.org/w/index.php?title=Wikipedia:Reducing_consensus_to_an_algorithm&diff=889397233&oldid=prevParcly Taxel: Navbox2019-03-25T12:53:30Z<p>Navbox</p>
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</table>Parcly Taxelhttps://en.wikipedia.org/w/index.php?title=Wikipedia:Reducing_consensus_to_an_algorithm&diff=882402238&oldid=prevSMcCandlish: creating essay2019-02-08T20:45:36Z<p>creating essay</p>
<p><b>New page</b></p><div>{{Essay|sc=WP:CONALGO|cat=Wikipedia essays on consensus}}<br />
{{Nutshell|While consensus formation on Wikipedia cannot {{em|literally}} be reduced to a mathematical function, the likelihood of success of a proposition in a content dispute is actually fairly simple to predict with a model.}}<br />
<br />
One might think at first that a general model of [[Wikipedia:Consensus|Wikipedia consensus]] formation would look something like:<br />
{{block indent|1=<br />
{{nowrap|1=A = N * R}}<br />
}}<br />
<br />
where:<br />
<br />
* A = argument strength/credibility<br />
* N = number of relevant [[Wikipedia:Verifiability|sources]] supporting the argument<br />
* R = the [[Wikipedia:Identifying reliable sources|reliability of the sources]].<br />
<br />
It's not really this simple. Each of the sources (call them S<sub>1</sub>, etc.) has its own R value (R<sub>1</sub>, etc., best expressed as a decimal value, where 0 is garbage and 1 is the most reliable source imaginable), so it would really need to be a recursive function to determine an adjusted source value for each source. But we also need to give a bit of extra [[WP:Due and undue weight|weight]] for providing more sources.<br />
<br />
This is more like it:<br />
<br />
{{block indent|1=<br />
{{nowrap|1=A = ((S<sub>1</sub> * R<sub>1</sub>) + (S<sub>2</sub> * R<sub>2</sub>) ...) / (N - (N / 10))}}<br />
}}<br />
<br />
Key:<br />
<br />
* A = argument strength/credibility<br />
* S<sub>{{var|x}}</sub> = an individual [[Wikipedia:Verifiability|source]]'s relevance (how well it supports argument A)<br />
* R<sub>{{var|x}}</sub> = [[Wikipedia:Identifying reliable sources|reliability]] of that source<br />
* N = number of relevant sources supporting the argument<br />
<br />
In plain English: Each source is assigned a contextual value, a combination of relevance to supporting the argument and reliability (reputability) of the source. These values are added together, then divided by number of sources presented, to produce an average. This step accounts for an increasing number of sources in support of the argument actually making the argument stronger, by slightly reducing the amount by which the relevance-and-reliability total is divided (in this model, for every ten sources you get a 1/10 bonus to argument credibility).<br />
<br />
This is just a {{lang|de|[[Gedankenexperiment]]}}, since we have no objective way to assign numeric S and R values. Still, this {{em|does seems to fairly accurately model how we settle content disputes generally}}, if you reduce the process to statistical outcomes.<br />
<br />
The more {{em|and}} better your sources are, the more your view will be accepted by consensus, all other things being equal. (Once in a while they are not equal, e.g. when a political or other [[WP:FACTION|faction]] has seized control of an article for the nonce and simply rejects ideas they don't like regardless of the evidence, until a [[WP:Noticeboard|noticeboard]] steps in and undoes the [[WP:Ownership of content|would-be ownership]] of the page.)<br />
<br />
Given a non-staggering sample size of sources, the model even accurately captures the negative effect on A (credibility) when trying to rely on any obviously terrible sources even if other sources are high-end. Every source that does not have an R value close to 1 will drag down the average (much like how a failing grade on one exam or paper out of 10 in a class will significantly lower your overall grade even if you got straight ''A''s on all the rest of them).<br />
<br />
It's not quite a perfect model, since it doesn't account for the fact that citing 100+ really terrible sources for a [[Wikipedia:Fringe theories|nonsense position]] ("[[Bigfoot]] is real", etc.) just makes you look crazy; the factoring of the effect of the number of sources is too simplistic.<br />
<br />
[[Category:Wikipedia humor]]</div>SMcCandlish