ABSTRACT
This paper builds on feminist elaborations of Bernstein’s code theory to engage in a series of thought experiments with interview data produced during a co-inquiry design-based research intervention project. It presents three accounts of thinking/writing with data. Our purpose in presenting three different accounts of interview data is to demonstrate the relation between theory and empirical data. In the first two accounts, interview data are interpreted and performed through the lens of theory. By contrast, in the third account attention is paid to the ways in which care is practised not only in terms of policy enactment, but also research enactment. Empirical data are not moulded to fit generalisable theoretical frameworks. Rather, empirical data push back on theoretical concepts in a collaborative thought experiment.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1 Twelve schools participated in the project, three high schools and nine primary schools, and seven of the nine primary school principals were female. In this paper, we pay particular attention to the practices of the female principals as they all had long experiences of working in high-poverty communities.
2 The research team comprised two chief investigators (Authors 1 and 3), two partner investigators, six school-based researchers, and three research assistants (all with doctoral qualifications). Only two members of the research team were male, a Partner Investigator and a Research Assistant.
3 Reference to the gradient of colours from red to green, with dark red signally significantly below average learning outcomes, and dark green signally significantly high in learning outcomes.
4 These contradictory and ambivalent responses to managerialist discourses of data-driven accountability and performativity have also been covered in recent reports prepared by professional associations and teachers' unions (see Canvass Report Citation2013; Queensland Teachers Union Citation2015).
5 An area well known for high levels of unemployment, drug use, violence, and public housing.