whofundsyou.org

Who Funds You? was a British volunteer-run project that sought to rate and promote transparency of funding sources of think tanks. The project scored think tanks according to four criteria, namely whether the organisation discloses its income, whether it publishes financial details online, whether individual donors and the amounts of each donation are published, and whether corporate donors are named and the amounts of each donation published. The project's first report into think tank transparency was published in June 2012. According to Martin Bright of The Spectator, the "exercise seems to demonstrate that left-leaning think tanks are more transparent than right-wing ones". The last report was published in October 2019 and the website is no longer being regularly updated, although people can still report if any organisation's transparency has improved since the final report. More information...

Multilingual Wikipedia

In June 2020 the website whofundsyou.org was on the 167,231st place in the ranking of the most reliable and popular sources in multilingual Wikipedia from readers' point of view (PR-score). If we consider only frequency of appearance of this source in references of Wikipedia articles (F-score), this website was on the 193,749th place in June 2020. From Wikipedians' point of view, "whofundsyou.org" is the 180,607th most reliable source in different language versions of Wikipedia (AR-score).

The website is placed before coastlinejournal.com and after cubagenweb.org in multilingual PR ranking of the most reliable sources in Wikipedia.

PR-score:
167,231st place
104,088
-9,003
AR-score:
180,607th place
13,473
+72
F-score:
193,749th place
32
+1

English Wikipedia (en)

PR-score:
92,172nd place
104,065
-8,987
AR-score:
86,813th place
13,450
+65
F-score:
80,367th place
30
0

Portuguese Wikipedia (pt)

PR-score:
217,700th place
22
-16
AR-score:
206,514th place
22
+6
F-score:
107,651st place
2
+1

BestRef shows popularity and reliability scores for sources in references of Wikipedia articles in different languages. Data extraction based on complex method using Wikimedia dumps. To find the most popular and reliable sources we used information about over 200 million references of Wikipedia articles. More details...