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From Wikipedia, the free encyclopedia
< Wikipedia:Autoconfirmed article creation trial

Report written by: Morten Warncke-Wang , with Ryan Kaldari and Danny Horn

The Autoconfirmed article creation trial (also known as "ACTRIAL") is a six-month trial that ran on the English Wikipedia from September 14, 2017 to March 14, 2018. During the trial, article creation was limited to users with autoconfirmed status (at least ten edits and at least four days since registration). Studying the first two months of the trial, our findings are:

We expand on these findings and provide key questions for follow-up discussions both amongst members of the English Wikipedia community as well as the Wikimedia Foundation.

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Screenshot of the New User Landing Page .

The Autoconfirmed article creation trial (also known as "ACTRIAL") is a six-month trial that ran on the English Wikipedia from September 14, 2017 to March 14, 2018. During the trial, article creation was limited to users with autoconfirmed status, meaning they had made at least ten edits and the account was at least four days old. When new editors tried to create a new page, they were redirected to a landing page offering links to the user's sandbox, a task recommendation page, and using the Article Wizard to create the page in the Draft namespace. Prior to the trial, article creation was available to anyone with a registered account.

This trial has a long history. Restrictions on who could create articles on the English Wikipedia were first put in place in December 2005, when shop online cheap marketable Versace crocoembossed Derby shoes for cheap for sale visa payment cheap sale sast bvtpFHsq
(see also Signpost coverage ) that users without accounts could no longer create articles. A proposal to further restrict article creation to users with autoconfirmed status was put forth and passed in 2011. A second proposal determined that the trial should run for six months. The Wikimedia Foundation declined to implement this ( get to buy online Dorateymur opentoe buckled mules pick a best cheap price 90NGOmfVK8
), and instead helped develop the Page Curation extension to make it easier to patrol new article creations.

The trial resurfaced again in 2017, at which time an ad-hoc consortium of employees of the Wikimedia Foundation did a study of the backlog of articles needing review and published a report . After discussing this report with the community, the WMF agreed to implement the trial in collaboration with the community and study the results. The WMF devoted resources and hired a researcher to work on designing the study and perform the analysis of the effects of the trial. The study was designed in collaboration with the community on both the English Wikipedia and Meta-wiki in order to determine how to best study the effects of the trial.


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Recognize the fundamental intractability of the problem here in the general case: in essence, one would like to capture a nearly infinite number of unique, individual, personalized performances (or, for the second challenge, rather than performances) from an algorithmic system at any given point in time. For many real-world systems, the sheer scale of this task (and the incomprehensibility of the results at this scale) makes the objective hopeless and utterly unrealistic. Here, the real stewardship goal, which I will explore in more detail shortly, must be to capture some meaningful sense of the system’s behavior and results for the present and the future. Comprehensiveness is quixotic.

For some specific systems, perhaps used much less frequently and with very high stakes (many of the governmental rather than commercial examples, such as judicial sentence recommendations), capturing all the outcomes and at least partial inputs for these outcomes is actually quite feasible, and indeed in some cases probably is, or should be, legally required as a matter of fundamental governmental record-keeping and accountability. Such comprehensive record keeping is easiest with systems that are fairly transactional and have little or no path dependency; these systems represent important and likely tractable special cases. Note that even this last modest proposal is not without controversy, as many of the algorithmic systems are made available to governments by secretive commercial corporations, who use a variety of contractual means to aggressively avoid having such records created or made public, arguing that this is necessary to protect their intellectual property, trade secrets, and competitive positions [ 17 ].

There is an excellent paper by Sandvig and his colleagues on methodologies for auditing “algorithms” (Sandvig, , 2014); parts of that work parallel much of my thinking, though with more colorful and memorable terminology. This work also provides a helpful point of departure for thinking about approaches to genuinely documenting “algorithms,” as opposed to auditing them, and the way in which these two activities are importantly different. I will return to explore what Sandvig’s approaches can offer the enterprise of documentation later in this paper.

The impossibility of traditional comprehensive archiving

A thought experiment: Imagine that Facebook CEO Mark Zuckerberg suddenly recognizes and totally embraces the idea that stewardship of some version of at least the public portion of Facebook (whatever that may be) is profoundly important, and that the company needs to support and enable it. Facebook then offers a comprehensive record to one or more stewardship institutions — perhaps the Library of Congress, Harvard University, ... — and perhaps even some funding (one can always dream). How many petabytes, and how many square miles of data centers are necessary to support and provide any form of meaningful access to this data? The Library of Congress experience with the Twitter archive is an important cautionary tale here [ 18 ]. Even if the lawyers were to permit transfer of such a gift (improbable due to privacy and liability concerns, both on the contributing and receiving sides of the transaction), this arrangement will not work.

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