Clarity

Clarity

Clarity compares how 55 French newsrooms from the left, center and right cover the same stories, exposing where media framing diverges.

Screenshot of Clarity
Overview

Clarity is a French news product that publishes a daily digest of national and international affairs built from 55 newsrooms spread across the political spectrum. Rather than commissioning its own reporting, the Paris-based site clusters coverage of the same event across outlets, then displays how many of those outlets lean left, center or right. The premise is simple. A reader who follows a single outlet sees one version of the day. A reader who sees the split sees where the framing diverges. The homepage summarises the scale of the operation in a single line: 2,639 articles read, 55 newspapers and 65 topics in 24 hours.

Key Features
  • Spectrum bars on every card: each story carries a hard segmented bar showing the share of newsrooms by camp, for example 20 percent left, 28 percent center and 52 percent right on the day's lead story, alongside the raw count of outlets covering it.
  • Angles morts (blind spots): two parallel lists, one for stories the left is not covering and one for stories the right ignores. Entries specify the exact split, such as 8 newsrooms, 5 center and 3 right, with no left outlet at all.
  • Baromètre 2027: a presidential tracker that sizes candidate portraits by voting intention, drawn from 7 polls by 7 institutes collected between 12 and 22 October. Marine Le Pen leads at 36 percent, ahead of Jean-Luc Mélenchon at 18 and Raphaël Glucksmann at 15.
  • Media share of voice: a stacked bar comparing editorial attention against polling strength across the past seven days of coverage, showing Le Pen at 36 percent of presidential airtime and Mélenchon at 22.
  • Les débats: opposing readings of the same story presented side by side, each argument tagged with a camp label such as Porté à droite or Porté au centre and the number of newsrooms that pushed it.
  • Topic filters and feeds: the day's remaining coverage sorted into Politique, International, Société, Économie, Culture, Tech and Science, with an RSS feed and a newsletter for readers who prefer push over browsing.
How It Works

The editorial pipeline ingests articles from the 55 partner newsrooms within a 24 hour window, groups them into topic clusters and records the camp of each publishing outlet. The homepage then exposes three views of that dataset: the lead story with its spectrum bar, debate pairs where camps disagree, and blind spot lists where one camp stays silent. Every card links to a story page that gathers the underlying coverage in one place.

Who It's For

Clarity targets French readers who want to check how a story is framed before forming a view, along with journalists tracking rival coverage, political staffers monitoring message uptake, and media literacy teachers who need a concrete illustration of framing. Researchers will find the aggregate numbers useful, though the product is built for reading rather than bulk analysis.

Pros & Cons

The Good

  • Every story card carries a segmented spectrum bar that quantifies the left, center and right split of the newsrooms covering it.
  • The dedicated Angles morts section names the stories each camp ignores, turning media blind spots into a browsable daily list.
  • The Baromètre 2027 blends voting intention data from 7 polling institutes with a share of voice breakdown of presidential coverage.
  • Debate pairs place competing readings of the same event side by side, tagged with camp labels and the number of outlets behind each position.
  • Access is free and requires no account, with RSS and newsletter delivery for readers who want a daily roundup.

The Bad

  • Coverage is limited to French newsrooms and French-language output, so the framing comparison does not extend beyond that media market.
  • Collapsing outlets into left, center and right buckets flattens editorial nuance that a single label cannot capture.
  • There is no API or data export, which limits use by researchers who want to analyze the underlying coverage dataset.

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