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Jessica Baldwin-Philippi | Associate Professor | Fordham University — 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
rodrigozamith.com ↗	72 match 1 shared topics	Rodrigo Zamith, Associate Professor, University of Massachusetts Amherst	en	education	robotsllmsaihumans	emailphone	none
christiankrekel.com ↗	70 match 1 shared topics	Christian Krekel - Associate Professor of Behavioural Science	en	education	robotsllmsaihumans	emailphone	none
aimeewilliamson.net ↗	69 match 1 shared topics	Aimee Williamson \| Professor \| Suffolk University \| Aimee Williamson, Ph.D.	en	education	robotsllmsaihumans	emailphone	none
dominicpettman.com ↗	68 match 1 shared topics	Dominic Pettman – University Professor of Media and New Humanities, New School	en	education WordPress	robotsllmsaihumans	emailphone	none
aaupjmu.com ↗	68 match 1 shared topics	AAUP JMU – Local chapter of the American Association of University Professors at James Madison University, Virginia	en	education WordPress	robotsllmsaihumans	emailphone	none
milofsky1.com ↗	68 match 1 shared topics	CARL MILOFSKY – Professor of Sociology	en	education WordPress	robotsllmsaihumans	emailphone	none
aarontrammell.com ↗	67 match 1 shared topics	Aaron Trammell – Associate Professor of Informatics, UC Irvine	en	education WordPress	robotsllmsaihumans	emailphone	none
pankhurimalhotra.com ↗	67 match 1 shared topics	Pankhuri Malhotra – Assistant Professor, Michael F. Price College of Business, University of Oklahoma	en	education WordPress	robotsllmsaihumans	emailphone	none
studylast.com ↗	66 match 1 shared topics	StudyLast \| Buy & Sell university, college, school & professional study notes	en	education WordPress WooCommerce	robotsllmsaihumans	emailphone	none
larisacioaca.com ↗	66 match 1 shared topics	Larisa Cioaca – Assistant Professor of Management	en	education WordPress	robotsllmsaihumans	emailphone	none
agsak.org ↗	66 match 1 shared topics	ASSOCIATION OF GENDER STUDIES IN AFRICA – Promote women’s rights, gender equality and diversity in Africa	en	education WordPress	robotsllmsaihumans	emailphone	none
icuworldwide.com ↗	66 match 1 shared topics	Homepage - Inclusive Cultural University Worldwide	en	education WordPress WooCommerce	robotsllmsaihumans	emailphone	none
kwerb.com ↗	66 match 1 shared topics	Kevin Werbach \| Wharton Professor \| Blockchain, Gamification & Technology Policy	en	education	robotsllmsaihumans	emailphone	none
rogerxaustin.com ↗	66 match 1 shared topics	Roger Austin \| Instructor at University of Northern Colorado. Compositionist, rhetorician, husband, gamer, cat guy.	en	education WordPress	robotsllmsaihumans	emailphone	none
aftabomer.org ↗	66 match 1 shared topics	Aftab Omer \| President, Meridian University	en	education WordPress	robotsllmsaihumans	emailphone	none
citizin.org ↗	66 match 1 shared topics	CitizIN: Indiana University	en	education	robotsllmsaihumans	emailphone	none
civicjournalismlab.org ↗	66 match 1 shared topics	Civic Journalism Lab – at Newcastle University	en	education WordPress	robotsllmsaihumans	emailphone	none
frostprepprogram.com ↗	66 match 1 shared topics	Preparatory Program \| Frost School of Music \| University of Miami	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.