• Collectors are as confused as you are about that $1.56M Super Mario 64 sale | Ars Technica
    https://arstechnica.com/features/2021/07/collectors-are-as-confused-as-you-are-about-that-1-56m-super-mario-64-s

    But for newcomers from other collectible spaces, this kind of quality-based price premium is relatively common. “In other spaces such as comics, coins, or sports cards, and many other collectibles, the difference between the second-highest grade and the highest grade can be a drastic difference in value and sometimes much more,” Wata Games CEO Ryan Sabga told Ars. “Attaining the finest known example from a condition standpoint drives a certain type of collector’s behavior, specifically the collector who wants the absolute best. The collectible video game market is no different.”

    #jeu_vidéo #jeux_vidéo #culture #collection #heritage_auctions #wata_games #record #analyse #zelda #the_legend_of_zelda #mario #super_mario_bros #mario_64 #jeu_vidéo_zelda #jeu_vidéo_the_legend_of_zelda #jeu_vidéo_mario #jeu_vidéo_super_mario_bros #jeu_vidéo_mario_64 #excellence #rareté

  • The secret lives of Google raters | Ars Technica
    https://arstechnica.com/features/2017/04/the-secret-lives-of-google-raters

    Who are these raters? They’re carefully trained and tested staff who can spend 40 hours per week logged into a system called Raterhub, which is owned and operated by Google. Every day, the raters complete dozens of short but exacting tasks that produce invaluable data about the usefulness of Google’s ever-changing algorithms. They contribute significantly to several Google and Android projects, from search and voice recognition to photos and personalization features.

    Few people realize how much these raters contribute to the smooth functioning act we call “Googling.” Even #Google engineers who work with rater data don’t know who these people are. But some raters would now like that to change. That’s because, earlier this month, thousands of them received an e-mail that said their hours would be cut in half, partly due to changes in Google’s staffing policies.

    Though Google boasts about its army of raters, the raters are not Google employees. Instead, they are employed by firms who have contracted them to Google, full time, for years on end. These raters believe that Google has reaped significant benefits from their labor without ensuring their jobs are secure and stable. That’s why 10 raters came to Ars Technica to tell the story of what their lives are really like.

    Du #digital_labor derrière les requêtes Google (et de la politique salariale de cette dernière)

    • The hidden human labour behind search engine algorithms
      http://blogs.lse.ac.uk/businessreview/2017/04/22/the-hidden-human-labour-behind-search-engine-algorithms

      The algorithmic production process requires work from highly trained professionals, such as top-level computer scientists and software engineers. Their work also becomes entangled with the input of low-skilled workers necessary for the customisation, testing, adaptation and sustainability of search in local markets worldwide.

      At least three types of search labour can be identified in Google’s global production process. First, the paid work of in-company engineers. This is the most celebrated aspect of algorithmic production and a major part of the story of Google’s technical superiority. Second is the non-paid labour of internet users, which contributes to value generation of the company. Simply put, the more people use the search engine, the more data the company collects, analyses, packages, and ultimately sells to advertisers. Third is the least transparent and discussed labour performed by “search quality raters” and “precision evaluators” hired via third party companies specialised in crowdsourcing global workforces. Google performs so-called precision evaluations and quality assessments of algorithmic changes on a regular basis. According to the latest data published by the company, it performs around 40,000 evaluations a year.

      (…)

      Unpacking the layers of labour processes behind algorithmic production has wide scholarly implications and potential policy impact in the field of digital literacy, market competition, transparent, fair, innovative and open digital economy. In the past few years, multiple European Union anti-trust investigations targeted three key areas: Google’s comparison shopping service, pre-installation of Google’s applications and services on Android OS, and restriction of third-party websites from displaying search ads from Google’s competitors.

      Google built its public image on separating the so-called organic, or “untampered” search results, from paid search results or ads. This division becomes less visible from a labour perspective. Tracing and mapping the input of precision evaluators delivered for algorithmic calculations of highly skilled engineers is hidden behind a wall of trade secrets. Thus the algorithmic ranking problem ceases to be a technical problem. Transparency of algorithmic calculations is also a political and economic issue since it affects visibility of actors seeking public exposure and impacts the advertising revenue flow.