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LeadAfrik Public Economics Hub — Finance, Economics & Data Tools From Africa — 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 Industry →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
sibieta-econ-ed.com ↗	67 match 1 shared topics	Sibieta Economics of Education	en	education-industry WordPress WooCommerce	robotsllmsaihumans	emailphone	none
economicsense.co.uk ↗	67 match 1 shared topics	Economics Training and Consulting - making sense of economics	United Kingdom en	education-industry WordPress	robotsllmsaihumans	emailphone	none
ctale.org ↗	66 match 1 shared topics	Connecting economics educators	en	education-industry WordPress	robotsllmsaihumans	emailphone	none
myeconoverse.com ↗	66 match 1 shared topics	EconoVerse – Transforming economics education with research-based resources, AI-enhanced tools, and bespoke support for teachers, departments, and schools.	en	education-industry WordPress	robotsllmsaihumans	emailphone	none
eml-learning.co.uk ↗	66 match 1 shared topics	Economics Courses & Training Center \| CSL Approved Courses \| EML Learning	United Kingdom en	education-industry Umbraco	robotsllmsaihumans	emailphone	none
analyticsforschools.com.au ↗	65 match 1 shared topics	Analytics For Schools - School Analytic Dashboards & Data Analytics	Australia en	education-industry WordPress	robotsllmsaihumans	emailphone	none
dadaschoolsgov.org ↗	65 match 1 shared topics	Miami-Dade County Public Schools - Procurement Services	en	education-industry Weebly	robotsllmsaihumans	emailphone	none
siewonkim.com ↗	65 match 1 shared topics	Sie Won Kim Economics Texas Tech University	United States~ en	education-industry Drupal	robotsllmsaihumans	emailphone	none
meet-toby-watson.com ↗	64 match 1 shared topics	Toby Watson: From Finance to Education at Excalibur	en	education-industry WordPress	robots llmsaihumans	emailphone	none
simlabs360.com ↗	64 match 1 shared topics	SimLabs - Educational Finance Simulation Platform	en	education-industry	robotsllmsaihumans	emailphone	none
primeledgeracademy.com ↗	64 match 1 shared topics	PrimeLedger Academy \| Democratizing Finance Education	en	education-industry	robotsllmsaihumans	emailphone	none
definable.com ↗	64 match 1 shared topics	Definable Solutions \| Data-Driven Insights for Schools & Local Governments	en	education-industry	robotsllmsaihumans	emailphone	none
lemeic.com ↗	64 match 1 shared topics	2026 International Conference on Law, Economics, and Modern Education (LEME 2026)	en	education-industry	robotsllmsaihumans	emailphone	none
learnpally.com ↗	64 match 1 shared topics	Learnpally Finance \| Education \| Workplace	en	education-industry	robotsllmsaihumans	emailphone	none
mcnastrategy.com ↗	64 match 1 shared topics	McNaStrategy - Higher Education Finance & Operations Consulting	en	education-industry	robotsllmsaihumans	emailphone	none
learning-deck.com ↗	64 match 1 shared topics	Learning Deck \| Tools for Thinking. Systems for Leading.	en	education-industry	robots llmsaihumans	emailphone	none
leannethomasanalytics.com ↗	64 match 1 shared topics	LeAnne Thomas \| Data Analyst Portfolio	en	education-industry Sanity	robotsllmsaihumans	emailphone	none
myschoolsuite.com ↗	64 match 1 shared topics	My School Suite - Free Student Information System for West African Schools	en	education-industry	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.