在社會科學領域之中，「瞭解事實，還原真相」，為研究者必須釐清、但卻可能是甚為棘手的問題，本研究以二○○二年六月二十一日立法院對於考試院正、副院長行使同意權為分析案例，嘗試藉由量化與質化交互為用的「跨層推論」（cross-level inference）研究方法，推估各政黨與無黨籍立法委員的投票表決行為。在這件備受矚與爭議的案例中，我們透過「集體層級資料」（aggregate-level data）的分析與新聞媒體的質化訊息，還原立法院對於考試院正副院長行使同意權的實際面貌。基本上，相關推論結果甚為「穩定」（robust），儘管與若干政治人物所宣稱的情形，差距甚遠。在結論中，本文提出該研究方法對於爾後學術研究的意涵。

　　　　　Social scientists constantly face the challenge of recovering information from messy and/or limited data. This article advocates a backward-elimination approach to cross-level inference hat takes full advantage of known auxiliary data to recover unobserved and yet crucial information. Through examining the controversial case of the Legislative Yuan's Consent Vote to the Nominees of the President and Vice-President of the Examination Yuan on June 21,2002, we show how to solve the puzzle of "who abstained in the vice-president nominee's consent vote" by inferring the voting patterns of each party's legislators from aggregate vote counts and news reports. Our solution is quite robust to various assumed scenarios despite the contrary claims made by politicians and pundits. We thus conclude that political scientists can expand their academic landscape by making creative use of this rich arsenal of research methodology.