Pinkas haKehilot

Pinkas haKehillot or Pinkas Ha-kehilot, (Hebrew: פנקס הקהילות; notebook of the [Jewish] communities; plural: Pinkasei haKehillot) Encyclopedia of Jewish Communities from Their Foundation till after the Holocaust,[2] is the name of each volume of a series presenting collected historical information and demographic data on Eastern European countries' Jewish communities, most of which were depopulated and whose populations were exterminated in the Holocaust. Pinkasei haKehillot is one of the most important projects undertaken by Yad Vashem in Jerusalem, concisely documenting this aspect of the history of the Holocaust.[3][4]

Pinkas haKehilot
Book cover, series, sample.[1]
Original titleפנקס הקהילות
CountryIsrael
LanguageHebrew and Yiddish
SubjectHistory of the Holocaust
PublisherYad Vashem

Content

Each volume of Pinkas Hakehillot is produced geographically, with locale names in Yiddish as well as the local language's version. The content is composed of collected documents, lists, personal memoirs in their original unedited form, historical accounts and essays devoted to the life of Jewish communities from antiquity until the present, including maps and period photographs. The Pinkas attempts to illustrate "the life that once was and is no more".

Awards

In 1973, the project was awarded the Israel Prize, for its special contribution to society and the State.[5] It receives financial support from the Memorial Foundation for Jewish Culture.[3]

Notes and references
  1. Book sample: The Communities of Lodz and its Region: List of the Communities, 1976, Yad Vashem, Jerusalem, 297 pages, Hebrew
  2. YIVO Institute for Jewish Research
  3. KOL haKEHILA, The Newsletter of the Jewish monuments of Greece
  4. "Rubin Mass Publishing, Israeli Books - Jewish Books all Israel books". Archived from the original on 2010-07-25. Retrieved 2010-10-19.
  5. "Israel Prize Official Site - Recipients in 1973 (in Hebrew)".
gollark: I guess it's possible that even one which doesn't know about parties might accidentally be biased due to (hypothetically, I don't know if this is true) one party being popular in low-density areas and the other in high-density, or really any other difference in locations.
gollark: You don't actually need simple shapes very badly as long as you have an algorithm which is not likely to be biased.
gollark: Okay, rearrange the states so they're square.
gollark: A simple if slightly inaccurate way would be some kind of binary space partitioning thing, where (pretending the US is a perfect square) you just repeatedly divide it in half (alternatingly vertically/horizontally), but stop dividing a particular subregion when population goes below some target number.
gollark: The more complex the algorithm the more people might try and manipulate it. The obvious* solution is to just split up the country by latitude/longitude grid squares.
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