#intersectional
Live, measured metrics for the hashtag #intersectional from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #intersectional
This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.
Day-by-day usage
measured · fosstodon.org (Mastodon public tags API) · fetched 2026-09-27 21:58 UTC1 uses by 1 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · fosstodon.org (Mastodon public search API) · fetched 2026-09-27 21:58 UTCLive pulse
measured · fosstodon.org (Mastodon tag timeline) · fetched 2026-09-27 21:58 UTCEverything below is measured over the latest 40 public posts (spanning ~4873 hours).
Posting hours (UTC) — busiest: 16:00
Languages: English (39) · German (1)
Avg boosts / post: 1.4
Top of the latest posts
Equal rights for others does not mean fewer rights for you. #intersectional #mentalhealth #socialjustice #humanrights #equity #stigma #mentalhealthmatters #ymhc
RE: https://mstdn.social/@markhburton/117259636877475621 🗣THIS IS WHAT REAL #FEMINISM LOOKS LIKE #antifa #antiracist #antisexist #intersectional
The cultural iceberg. #intersectional #mentalhealth #ymhc
What “intersectional” means
WikipediaIntersectionality is an analytical framework for understanding how groups' and individuals' social and political identities result in unique combinations of discrimination and privilege. Examples of these intersecting and overlapping factors include gender, caste, sex, race, ethnicity, class, sexuality, religion, disability, physical appearance, and age. These factors can lead to both empowerment and oppression.
“Intersectionality” on Wikipedia (CC BY-SA) →#intersectional across platforms
every network with a public tag surfaceFollow #intersectional straight to each platform’s own tag page. Where a platform publishes open data we measure it above; the rest lock their numbers behind paid APIs, so we link rather than guess.
Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/intersectional