A European lens upon adult and lifelong learning in Asia

In this article, we seek to assess the extent to which adult and lifelong learning policies and practices in Asia have distinctiveness by comparison to those found in western societies, through an analysis of inter-governmental, national and regional policies in the field. We also inform our study through the analysis of the work of organisations with an international remit with a specific focus on Asia and Europe. In one case, the Asia–Europe Meeting Lifelong Learning (ASEM LLL) Hub has a specific function of bringing together researchers in Asia and Europe. In another, the PASCAL Observatory has had a particular focus on one aspect of lifelong learning, that of learning cities, with a concentration in its work on Asia and Europe. We focus on learning city development as a particular case of distinction in the field. We seek to identify the extent to which developments in the field in Asia have influenced and have been influenced by practices elsewhere in world, especially in Europe, and undertake our analysis using theories of societal learning/the learning society, learning communities and life-deep learning. We complement our analysis through assessment of material contained in three dominant journals in the field, the International Journal of Lifelong Education, the International Review of Education and Adult Education Quarterly, each edited in the west

Observing many researchers using the same data and hypothesis reveals a hidden universe of uncertainty

This study explores how researchers’ analytical choices affect the reliability of scientific findings. Most discussions of reliability problems in science focus on systematic biases. We broaden the lens to emphasize the idiosyncrasy of conscious and unconscious decisions that researchers make during data analysis. We coordinated 161 researchers in 73 research teams and observed their research decisions as they used the same data to independently test the same prominent social science hypothesis: that greater immigration reduces support for social policies among the public. In this typical case of social science research, research teams reported both widely diverging numerical findings and substantive conclusions despite identical start conditions. Researchers’ expertise, prior beliefs, and expectations barely predict the wide variation in research outcomes. More than 95% of the total variance in numerical results remains unexplained even after qualitative coding of all identifiable decisions in each team’s workflow. This reveals a universe of uncertainty that remains hidden when considering a single study in isolation. The idiosyncratic nature of how researchers’ results and conclusions varied is a previously underappreciated explanation for why many scientific hypotheses remain contested. These results call for greater epistemic humility and clarity in reporting scientific findings