不完全訊息下受歧視族群分佈之分析

Analysis on Distribution of Discriminated Subgroups under Incomplete Information

王婉如(WAN-JU WANG)

指導教授 ： 莊委桐

國立臺灣大學/社會科學院/經濟學研究所/碩士(2013年)

https://doi.org/10.6342/NTU.2013.03012

摘要

在多元種族的國家裡，可以很容易觀察到族群分佈有明顯的聚集現象。
一個普遍的解釋是人先天偏愛與自己同類的人，
本文說明就算人不先天偏愛同類族群，且就算所有族群本質無異，
如果人對異族群的本質相對無知，
且只能根據實際觀測資料評估是否該排斥異族群，
少數族群仍會產生群聚的現象。
因為在隨機性的干擾下，群聚能減低少數族群被歧視的機率，從而產生某種程度的聚集。
此外，文中也探討重要參數如何影響聚集的程度，並用模擬的方式驗證。

關鍵字

網路 ； 歧視 ； 群聚 ； 不完全訊息

並列摘要

It is easy to observe the phenomenon of racial clustering in a multiracial society.
A common explanation is people prefer their own kind.
This paper shows that even people not prefer their own kind and even all people are the same, the minority group still tends to cluster if we are ignorance of other subgroups and can decide to discriminate other subgroups or not only based on observable information.
In this situation, clustering can reduce the probability of being discriminated under stochastic condition.
Also, this paper illustrates how the crucial parameter impact on the degree of clustering and testifies the results with simulation.

並列關鍵字

networks ； discrimination ； clustering ； incomplete information

參考文獻

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