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題名:重新探索臺灣選民的政黨認同與政黨態度— 外顯與內隱測量方法的比較分析
作者:楊琇雯
作者(外文):Yang, Hsiu-Wen
校院名稱:國立成功大學
系所名稱:政治學系
指導教授:蒙志成
學位類別:博士
出版日期:2022
主題關鍵詞:政黨認同政黨態度內隱聯結測驗公民投票社會認同理論Party IdentificationParty AttitudesImplicit Association TestReferendumSocial Identity Theory
原始連結:連回原系統網址new window
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民主選舉下的政黨競爭會出於敵我分立的心理狀態,找到群眾的「政黨認同」視為其中關鍵心理因素,過去測量政黨認同時,慣用單一題的自陳問卷,但不少民眾回答自己沒有政黨認同,但這卻不代表自己不會受政黨影響,背後其實有「隱性的政黨態度」因素,如果無法區分這群人是否輕微的政黨傾向,會造成在分析上,難以解釋群眾敵對心理及其行為。因此,本論文的問題意識在於,能否藉由不同測量方法,重新探索臺灣選民的政黨認同與政黨態度為何?並嘗試以2021年的公民投票議題,討論內外團體的投票行為。
在顯性與隱性的測量方法上,各有突破,採用問卷調查併心理測量之研究設計。在問卷調查法,問卷題目設計旨在測量政黨認同的團體心理,將納入Huddy、Mason和Aarøe(2015)的「表意性政黨認同量表」、Bankert(2020)的「負面」表意性政黨認同量表,但因Huddy他們所提出的工具性政黨認同是直接測量個人自由或保守的政黨立場測量,臺灣選民不熟悉意識形態定義,難以自我歸類,因而本研究將自行創設「工具性政黨認同量表」;而在心理測量中,嘗試使用內隱聯結測驗(Implicit Association Test, IAT),取得全體選民們的真實政黨傾向,將傾向的基礎分成「表意性、情緒性、道德性、工具性」等四個種類的政黨傾向。
因IAT作為測量內隱態度的工具時,可以避免自我掩飾(self-present)的問題,因而能檢測傳統測量方法的缺漏。結果發現,有政黨認同的民眾在回應認同「強度」時,會弱化自身的認同強度,從而導致測量不夠精確,建議改採Huddy等人的表意性多題組測量強度,效果較好。關於內外團體的投票行為,有政黨認同者會更願意參與公民投票,出現支持內團體議題立場的公民投票行為;當政黨傾向偏好民進黨時,降低投下同意票的機率,偏好國民黨時,則提高投下同意票的可能,個人的意識形態立場反而並非議題投票的主因,而且在投票日前,政黨早已經形塑個人議題立場。在測量比較上,工具IAT比起顯性模式,更可以預測公民投票行為,並證實個人政黨認同有所謂的「工具性」心理基礎,也就是政黨對於民眾來說是一種達成政策的工具,支持與自己相同政策立場的政黨是為了獲得利益回報,而不只是一種情感的依戀。
本研究利用多元測量方法重新探索政黨認同與政黨態度,證實新式多題組的量表與IAT測量方法都能夠有效解釋2021年公民投票行為。
Given that inter-party competition often occurred during elections among democratic countries, this competition often leads to a situation in which people divided each other into in-groups and out-groups based on political orientations. Ways to measure and quantify this "party identification" of voters were vital for political studies.
The conventional political studies often collect the data of party identification with subject's answer to single question in a series of self-report questionnaires. Although numerous people listed themselves as independents in term of political partisanship, this rarely meant they were independent or unbiased toward political issues. There exists an "implicit political party attitude" in the psyche of each subject. If we ignore the political party attitudes of these subjects, it would be difficult to account for the inter political group hostilities among the subjects. Therefore, the emphasis of this dissertation was to revisit the political party identification and political party attitudes among Taiwanese voters, with a different set of measurement methods. To better support my attempts of gauging political identification by using explicit and implicit attitude measurements, this study would further analyze the voting behavior of subjects along with the in-group/out-group arguments on the case of 2021 Taiwan's referendum.
This dissertation applied the questionnaire survey and psychological measurement to the participants from a purposive samping(N=365). The questionnaire survey used a multi-item partisan identity scale as the measurement model for overt partisanship to assess respondents’ implicit partisanship, proposed by Huddy, Mason and Aarøe(2015) and Bankert (2020). Huddy et al. (2015) also suggested the instrumental partisanship measurement model by subject's liberal and conservative ideology to extend the theoretical concept of party identification. However, since Taiwanese subjects were not familiar with this model's ideological measurement, it was not workable to ask them to identify themselves' instrumental partisanship accordingly. Therefore, instead of ideological measurement, this study creates the "instrumental partisanship scale" in a multi-item format capable and appropriate for measuring the instrumental partisanship of Taiwan electorates.
This study's psychological measurement applied the Implicit Association Test (IAT) to measure the more accurate political party related attitudes of all voters. I classified the gathered data into four types of party attitudes: expressive, emotional, moral, and instrumental.
This study conducted two data collection design of explicit attitude measurement: one is derived from the single-question method, the other is from multi-question method. The data analysis reveals an not uncommon challenge that a respondent is easily to mislead or hide his/ her party identification under the inquiry of a single-question method design. Therefore, the data from the single -question method may not reflect the true extent of a subject’s political identification; in contrast, with the collaboration of the IAT measurement, the multi-question method performed better in gauging the true extent of the subject’s party identification.
People who identified with a particular political party increased the likelihood of participation in the referendum, and their voting behaviors were in accordance with the position of the in-group while facing the same issues. When people preferred the DPP(Democratic Progressive Party), the probability of an approval vote was reduced; in contrast, when they preferred KMT(Kuomintang), the probability of an approval vote was increased. Before polling day, political parties were already shaping individual voter's positions on issues. Personal ideology was never play significant influence to this referendum voting. Compared to data from the explicit attitudes in the self-report questionnaires, the IAT measurement of implicit attitudes was more helpful in prediction of referendum ballot casting, in particular for those subjects claiming themselves as independent party identifiers. The IAT assessment also supported the argument that voters regarded political parties as "instrumental"; in the other words, voter supported not only the political party in alignment with his interests but also expected feedback for his support, contrary to the belief that support of political party was just an emotional attachment. This study re-visited party identification and party attitudes with multi-variate measurement methods.
The result confirmed that the new measurement scale, comprising multi-item questionnaires, and IAT measurement method could explain the voting behaviors of 2021 referendum.
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