Nice work if you can get it? The changing character of academic labour in Sweden and England

This paper considers recent attempts to introduce managerial reform in higher education. In exploring the issues the paper draws on an interviewing programme conducted with female and male academics in Sweden and England responsible for delivering change: heads of department, heads of division and principal lecturers. The aim is to examine the implications for the day-to-day work of academics arising from the reforms and to consider the gender implications. The paper conceptualises the areas of academic responsibility along the following dimensions identified by the academics themselves: dog work, tough work, care work, real work and nice work. In bringing into sharper focus the harsher realities of academe, and exploring the overlap and connectivity between gender and academic labour, it is argued that intellectual labour is hard work indeed, particularly for women.

Buy three but get only two: The smallest effect in a 2 × 2 ANOVA is always uninterpretable

Loftus (Memory & Cognition 6:312-319, 1978) distinguished between interpretable and uninterpretable interactions. Uninterpretable interactions are ambiguous, because they may be due to two additive main effects (no interaction) and a nonlinear relationship between the (latent) outcome variable and its indicator. Interpretable interactions can only be due to the presence of a true interactive effect in the outcome variable, regardless of the relationship that it establishes with its indicator. In the present article, we first show that same problem can arise when an unmeasured mediator has a nonlinear effect on the measured outcome variable. Then we integrate Loftus's arguments with a seemingly contradictory approach to interactions suggested by Rosnow and Rosenthal (Psychological Bulletin 105:143-146, 1989). We show that entire data patterns, not just interaction effects alone, produce interpretable or noninterpretable interactions. Next, we show that the same problem of interpretability can apply to main effects. Lastly, we give concrete advice on what researchers can do to generate data patterns that provide unambiguous evidence for hypothesized interactions.