u/lasushin

Data sources:
GDP per capita - Wellcome, The Gallup Organization Ltd. (2021). Wellcome Global Monitor, 2020. Processed by Our World in Data
https://ourworldindata.org/grapher/gdp-per-capita-maddison-project-database
Gini Coefficient - World Bank Poverty and Inequality Platform (2025) with major processing by Our World in Data
https://ourworldindata.org/grapher/economic-inequality-gini-index
% share of lifetime anxiety or depression - Bolt and van Zanden – Maddison Project Database 2023 with minor processing by Our World in Data
https://ourworldindata.org/grapher/share-who-report-lifetime-anxiety-or-depression

Data graphed using matplotlib with Python, code written with the help of codex.

I've recently created ClearFrame - an extension which highlights words in different colors depending on categories, and sorts them into types, such as clickbait, exaggeration, euphemisms, unsourced, authority, etc. I'd like feedback from those who often read news online or are otherwise tired of non-neutral language. Here are some options I'm considering:

• replacing biased words with neutral alternatives
• only highlighting biased words for educative purposes (could also be used for learning authorial choices/literary devices)
• removing biased words/blurring them entirely

Some things are easier to do than others. Many people told me they hate sarcasm, political bias but this may be unrealistic to implement without using AI, which has costs. I'd like to for now limit the extension to matching phrases, words and regex patterns so it can remain open-source for everyone to benefit from. So those 3 options are the main ones I'm considering.

This is still just an experiment/idea, so any feedback would be greatly appreciated!!!

https://chromewebstore.google.com/detail/clearframe/nkijmgimgocgagenbmgjjchaepjlcked