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William Jamal Richardson – Sociologist, Research Consultant, Science Fiction/Fantasy Writer — 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 Books And Literature →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
helenevanrossum.com ↗	67 match 1 shared topics	Helene van Rossum – Writer, educator, archival researcher	en	books-and-literature WordPress	robotsllmsaihumans	emailphone	none
annaadima.com ↗	66 match 1 shared topics	Anna Adima \| Writer, researcher and cultural practitioner in East Africa	en	books-and-literature Wix	robots llmsaihumans	emailphone	none
srltackitt.com ↗	66 match 1 shared topics	Saint-Rowan Tackitt – Cultural Anthropologist, Historian, Writer, Educator	en	books-and-literature WordPress	robotsllmsaihumans	emailphone	none
viviennekearns.com ↗	66 match 1 shared topics	Vivienne Kearns – Historical Fiction Writer from Dublin, Ireland	en	books-and-literature WordPress	robotsllmsaihumans	emailphone	none
danielsmithauthor.com ↗	66 match 1 shared topics	D.E. Smith – Author – Writer of historical fiction and more	en	books-and-literature WordPress	robotsllmsaihumans	emailphone	full · 12
danielfadlon.com ↗	66 match 1 shared topics	Daniel Fadlon — Writer & Researcher, Tel Aviv	en	books-and-literature	robotsllmsaihumans	emailphone	none
anviltext.com ↗	66 match 1 shared topics	Anvil - Text Editor For Fiction Writers	en	books-and-literature	robotsllmsaihumans	emailphone	none
1mmlibrary.com ↗	66 match 1 shared topics	The 1MM Library Initiative \| Library and Research Center of Western Pennsylvania, Supervised by Moosaa Richardson	en	books-and-literature WordPress	robotsllmsaihumans	emailphone	none
davebellous.com ↗	66 match 1 shared topics	Dave Bellous – Entrepreneur, technologist, cyclist, reader.	en	books-and-literature WordPress	robotsllmsaihumans	emailphone	none
deborahtomkinswriter.com ↗	66 match 1 shared topics	Deborah Tomkins fiction writer	en	books-and-literature WordPress	robotsllmsaihumans	emailphone	none
vivienmorgan.com ↗	65 match 1 shared topics	Vivien Morgan - Author, Lecturer and Communications Consultant \| Vivien Morgan	en	books-and-literature WordPress	robotsllmsaihumans	emailphone	none
heloisejones.com ↗	65 match 1 shared topics	Heloise Jones - Author & Alchemical Insight Consultant	en	books-and-literature WordPress	robotsllmsaihumans	emailphone	none
4fiction.com ↗	65 match 1 shared topics	4Fiction -- Search Fiction, Characters, Books, Media	en	books-and-literature	robotsllmsaihumans	emailphone	none
bryanglick.com ↗	65 match 1 shared topics	Bryan Glick – Writer, journalist, technologist	en	books-and-literature WordPress	robotsllmsaihumans	emailphone	none
katestuartauthor.com ↗	65 match 1 shared topics	Kate Stuart - Writing books and researching authorship	en	books-and-literature WordPress	robotsllmsaihumans	emailphone	none
spywrite.com ↗	65 match 1 shared topics	Spy Write – Reviewing and collecting spy fiction and nonfiction	en	books-and-literature WordPress	robotsllmsaihumans	emailphone	none
elementsofshortfiction.com ↗	65 match 1 shared topics	The Elements of Short Fiction – Practical Guide for Writers	en	books-and-literature WordPress	robotsllmsaihumans	emailphone	none
ercrichardson.com ↗	65 match 1 shared topics	E. R. C. Richardson – Storyteller of misbehaving characters	en	books-and-literature WordPress	robotsllmsaihumans	emailphone	full · 12

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.