Teachers’ recommendations for students’ educational careers and school track choices play an important role in students’ future academic performance. This is the case in Germany when it comes to teachers’ track recommendations at the end of primary school. On the basis of the students’ grades, primary school teachers recommend a secondary track (Nichtgymnasium or Gymnasium). These recommendations not only depend on the diagnostic but also on the predictive accuracy of teachers’ judgments. However, in some federal states students are allowed to select a different track than that recommended by the primary school teacher. Yet, recent research shows that students from families of a lower socio-economic-status (SES) more frequently attend less demanding secondary tracks and achieve lower test-scores compared to socio-economically privileged students (e.g., Boone & Van Houtte 2013; OECD 2013). Although there is ample evidence on the accuracy (e.g., Martin & Shapiro 2011) and on the predictive validity (e.g., Dollmann 2011) of teacher judgments, research has yet to evaluate both concepts together by taking medium- and long-range prediction studies into account.

Consistent with the evaluative framework for diagnostic screenings and batteries by Jenkins, Hudson and Johnson (2007) merely reporting predictive validity coefficients – efficacy – provides weak evidence for the predictive (classification) accuracy – effectiveness – of teachers' track recommendations. For this reason, the present study aims to expand the research perspective by theoretically and empirically describing the concept of predictive accuracy, particularly in contrast to the predictive validity and with special regard to teachers' academically oriented recommendations as loosely organized selecting measures. This research proposal focuses on three central questions: (1) How accurate are selecting measures that are almost exclusively based on teachers’ track recommendations when predicting students’ future academic achievement? (2) Are selecting measures more or less accurate when predicting the academic achievement of students from different socio-economic backgrounds on the basis of teachers’ track recommendations? (3) How is the predictive validity of selecting measures influenced by the interplay between teachers' track recommendations and students’ SES?

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