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Dylan Paré – Assistant Professor, Learning, Design, and Technology for Justice and Belonging — 18 websites ranked by shared content topics, category and on-page relevance.

Each result shows its full tech stack, contacts and AI-policy — not just a name · Browse all sites in Education →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
jasonprobey.com ↗	68 match 1 shared topics	Jason Robey – Assistant Professor	en	education WordPress	robotsllmsaihumans	emailphone	none
jeremiehoussineau.com ↗	68 match 1 shared topics	Jeremie Houssineau – Assistant Professor at the Nanyang Technological University	en	education WordPress	robotsllmsaihumans	emailphone	none
jenniferannehart.com ↗	68 match 1 shared topics	Jennifer Anne Hart – Assistant Professor, Wayne State University	en	education WordPress	robotsllmsaihumans	emailphone	none
thetattooedprof.com ↗	68 match 1 shared topics	The Tattooed Professor – History, Teaching, and Technology with a Custom Paint Job	en	education WordPress	robotsllmsaihumans	emailphone	none
mrjohngustafson.org ↗	67 match 1 shared topics	Linking Learning & Belonging	en	education WordPress	robotsllmsaihumans	emailphone	none
boknowzlearning.com ↗	66 match 1 shared topics	Bo Knowz Learning \| SEL & Belonging Consulting for Schools	en	education	robotsllmsaihumans	emailphone	none
wemolenmaker.com ↗	66 match 1 shared topics	Welmer E. Molenmaker \| Assistant Professor • Leiden University	en	education WordPress	robotsllmsaihumans	emailphone	none
deneilchristian.com ↗	66 match 1 shared topics	Deneil D. Christian, Ph.D., CFE – Dr. Deneil Christian is a criminal justice professor, researcher, and certified fraud examiner.	en	education WordPress	robotsllmsaihumans	emailphone	none
j4jalliance.org ↗	66 match 1 shared topics	Journey for Justice - Rooted in racial justice and education equity	en	education WordPress WooCommerce	robotsllmsaihumans	emailphone	none
digitalmontpelier.org ↗	66 match 1 shared topics	The Institute for Advanced Technology in the Humanities	en	education	robotsllmsaihumans	emailphone	none
melissatully.net ↗	65 match 1 shared topics	Melissa Tully – Associate Professor, Journalism and Mass Communication, University of Iowa	en	education WordPress	robotsllmsaihumans	emailphone	none
sjtylr.net ↗	65 match 1 shared topics	Wayfinder Learning Lab – Stephen Taylor – "Learning is about living, and as such is lifelong." Elkjaer.	en	education WordPress	robotsllmsaihumans	emailphone	none
cpi.edu ↗	65 match 1 shared topics	Central Pennsylvania Institute of Science and Technology – Discover A World of Opportunity	en	education WordPress Reaction Commerce	robotsllmsaihumans	email phone	none
werbach.com ↗	65 match 1 shared topics	Kevin Werbach \| Wharton Professor \| Blockchain, Gamification & Technology Policy	en	education	robotsllmsaihumans	emailphone	none
mehergarh.org ↗	65 match 1 shared topics	Mehergarh – A Center for Learning	en	education WordPress	robotsllmsaihumans	email phone	none
thiemobreyer.com ↗	65 match 1 shared topics	Thiemo Breyer – Professor of Phenomenology and Anthropology	en	education WordPress	robotsllmsaihumans	emailphone	none
singingnettle.org ↗	65 match 1 shared topics	Singing Nettle Forest Stewards – nonprofit learning program	en	education WordPress WooCommerce	robotsllmsaihumans	emailphone	none
marinalennon.com ↗	65 match 1 shared topics	Marina Lennon \| Learning Journey	en	education	robotsllmsaihumans	emailphone	none

How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

shared topics how many of the same fine‑grained content topics (IAB sub‑categories) both sites cover — the main signal.
same category whether they sit in the same business / industry category.
content & title how closely their titles and page descriptions line up in wording and meaning.

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.