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๐Ÿ‡น๐Ÿ‡ผ Taiwan /Elections & Politics

Ko Wen-je on Seeking Advice from Former Taipei Mayors

From Liberty Times · () Chinese

Translated from Chinese and summarized by DistantNews. Read the original for the full story.

At a glance

News Named sources Context piece
  • Taipei mayoral candidate Shen Po-yang intends to seek advice from former city mayors.
  • Ko Wen-je, a former Taipei mayor, suggested Chang Ching-sen could be Shen's advisor.
  • Shen Po-yang also plans to meet with former President Chen Shui-bian.

Taipei mayoral candidate Shen Po-yang has announced plans to consult with former city mayors as part of his campaign preparations. This outreach includes seeking insights from former President Chen Shui-bian, as well as previous Taipei mayors such as Ma Ying-jeou, Hau Lung-pin, and Ko Wen-je.

Responding to the news, Ko Wen-je, who served as Taipei mayor from 2014 to 2022, stated that he had no objection to Shen Po-yang seeking his advice. However, Ko noted that he is currently traveling in southern Taiwan and would likely be available for a meeting the following week. He also humorously suggested that Chang Ching-sen, a former minister without portfolio in the Executive Yuan, might serve as Shen's "military advisor."

Shen Po-yang, representing the Democratic Progressive Party (DPP), revealed his intention to meet with Chen Shui-bian in Tainan within the month. His consultation list spans across party lines, indicating a broad approach to gathering political wisdom. The candidate aims to leverage the experience of past city leaders to inform his mayoral bid.

When approached by reporters, Ko Wen-je was attending a Mid-Autumn Festival event in Yunlin County. He reiterated his availability for a meeting the following week and expressed openness to discussing any topic Shen Po-yang wished to raise. The former mayor indicated that the nature of the advice would depend on the questions posed by the candidate.

About this summary

Originally published by Liberty Times in Chinese. Translated, summarized, and contextualized automatically by DistantNews, with a note on how the source frames the story. Not individually reviewed before publishing. How this works.