attawapiskat.org

The Attawapiskat First Nation is an isolated First Nation located in Kenora District in northern Ontario, Canada, at the mouth of the Attawapiskat River on James Bay. The traditional territory of the Attawapiskat First Nation extends beyond their reserve up the coast to Hudson Bay and hundreds of kilometres inland along river tributaries. The community is connected to other towns along the shore of James Bay by the seasonal ice road/winter road constructed each December, linking it to the towns of Kashechewan First Nation, Fort Albany, and Moosonee Attawapiskat, Fort Albany, and Kashechewan operate and manage the James Bay Winter Road through a jointly owned corporation named after the Cree word for "our road" kimesskanemenow, the Kimesskanemenow Corporation. Attawapiskat is the most remote northerly link on the road to Moosonee. They control the reserves at Attawapiskat 91 and Attawapiskat 91A. More information...

Multilingual Wikipedia

In June 2020 the website attawapiskat.org was on the 962,652nd 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 463,606th place in June 2020. From Wikipedians' point of view, "attawapiskat.org" is the 907,662nd most reliable source in different language versions of Wikipedia (AR-score).

The website is placed before rumus-matematika.com and after abpmr.org in multilingual PR ranking of the most reliable sources in Wikipedia.

PR-score:
962,652nd place
6,799
-928
AR-score:
907,662nd place
1,633
+3
F-score:
463,606th place
10
0

English Wikipedia (en)

PR-score:
552,557th place
6,765
-929
AR-score:
487,351st place
1,566
+2
F-score:
213,626th place
9
0

Arabic Wikipedia (ar)

PR-score:
161,272nd place
33
0
AR-score:
152,214th place
66
0
F-score:
153,880th place
1
0

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...