title: Bayesian network classifiers in Weka

authors: Bouckaert, Remco R.

abstract: Various Bayesian network classifier learning algorithms are implemented in Weka [10].This note provides some user documentation and implementation details.
Summary of main capabilities:
_Structure learning of Bayesian networks using various hill climbing (K2, B, etc) and general purpose (simulated annealing, tabu search) algorithms.
_Local score metrics implemented; Bayes, BDe, MDL, entropy, AIC.
_Global score metrics implemented; leave one out cv, k-fold cv and cumulative cv.
_Conditional independence based causal recovery algorithm available.
_Parameter estimation using direct estimates and Bayesian model averaging.
_GUI for easy inspection of Bayesian networks.
_Part of Weka allowing systematic experiments to compare Bayes net performance with general purpose classi_ers like C4.5, nearest neighbor, support vector, etc.
_Source code available under GPL allows for integration in other systems and makes it easy to extend.

text: Bayesian network classifiers in Weka Various Bayesian network classifier learning algorithms are implemented in Weka [10].This note provides some user documentation and implementation details.
Summary of main capabilities:
_Structure learning of Bayesian networks using various hill climbing (K2, B, etc) and general purpose (simulated annealing, tabu search) algorithms.
_Local score metrics implemented; Bayes, BDe, MDL, entropy, AIC.
_Global score metrics implemented; leave one out cv, k-fold cv and cumulative cv.
_Conditional independence based causal recovery algorithm available.
_Parameter estimation using direct estimates and Bayesian model averaging.
_GUI for easy inspection of Bayesian networks.
_Part of Weka allowing systematic experiments to compare Bayes net performance with general purpose classi_ers like C4.5, nearest neighbor, support vector, etc.
_Source code available under GPL allows for integration in other systems and makes it easy to extend.

year: 2004-09-01

title: Identify Survey: Community and advocacy report

authors: Fenaughty, John

abstract: The Identify survey is the largest study focused on rainbow young people (aged 14-26) in Aotearoa New Zealand to date. This survey was live between February and August 2021. The research team is a diverse array of rainbow community youth organisations, leaders and researchers. The research team are united in our belief that excellent survey results can help inform ways in which we can improve rainbow lives in Aotearoa New Zealand and beyond. In total, 4784 rainbow young people and 434 of their allies took part in the survey. The findings in this report are based on the survey responses of rainbow young people.  Identify was very successful at generating a wide and diverse sample of rainbow young people, including 2045 (43%) who were currently in secondary education, 1640 (34%) who were in post-secondary education, and 1099 (23%) who were not in education but were either in paid or unpaid employment, or were unemployed. There was a good spread of ethnicities reported, and at a total-response level, 12% were Māori; 4% Pacific; 9% Asian; and 71% Pākehā, NZ European, or another European identity. There were also around 1% respectively of participants who were Middle Eastern, Latin American, African, or North American. For this age bracket, this distribution is disproportionally white and underrepresents Pacific populations, which is a limitation we recognise in our recommendations. Participants reported a wide array of gender identities and modalities. Broadly, 52% of participants were classified as cisgender women/girls (39%) or men/ boys (13%), 14% as trans men/boys or trans women/girls, 30% as non-binary and 4% as questioning their gender. Similarly, a wide array of sexualities was reported. Participants with intersex variations or variations of sex characteristics were also registered, accounting for approximately 1% of the cohort. Just over two in five participants were identified as disabled.

text: Identify Survey: Community and advocacy report The Identify survey is the largest study focused on rainbow young people (aged 14-26) in Aotearoa New Zealand to date. This survey was live between February and August 2021. The research team is a diverse array of rainbow community youth organisations, leaders and researchers. The research team are united in our belief that excellent survey results can help inform ways in which we can improve rainbow lives in Aotearoa New Zealand and beyond. In total, 4784 rainbow young people and 434 of their allies took part in the survey. The findings in this report are based on the survey responses of rainbow young people.  Identify was very successful at generating a wide and diverse sample of rainbow young people, including 2045 (43%) who were currently in secondary education, 1640 (34%) who were in post-secondary education, and 1099 (23%) who were not in education but were either in paid or unpaid employment, or were unemployed. There was a good spread of ethnicities reported, and at a total-response level, 12% were Māori; 4% Pacific; 9% Asian; and 71% Pākehā, NZ European, or another European identity. There were also around 1% respectively of participants who were Middle Eastern, Latin American, African, or North American. For this age bracket, this distribution is disproportionally white and underrepresents Pacific populations, which is a limitation we recognise in our recommendations. Participants reported a wide array of gender identities and modalities. Broadly, 52% of participants were classified as cisgender women/girls (39%) or men/ boys (13%), 14% as trans men/boys or trans women/girls, 30% as non-binary and 4% as questioning their gender. Similarly, a wide array of sexualities was reported. Participants with intersex variations or variations of sex characteristics were also registered, accounting for approximately 1% of the cohort. Just over two in five participants were identified as disabled.

year: 2022

title: The gown and the korowai: Maori doctoral students and the spatial organization of academic knowledge

authors: Middleton, Sue

subjects: culture

abstract: This paper draws on 38 student interviews carried out in the course of the team research project Teaching and Learning in the Supervision of Māori Doctoral Students. Māori doctoral thesis work takes place in the intersections between the Māori (tribal) world of identifications and obligations, the organisational and epistemological configurations of academia, and the bureaucratic requirements of funding or employing bureaucracies. To explore how students accommodate cultural, academic and bureaucratic demands, we develop analytical tools combining three intellectual traditions: Māori educational theory, Bernstein’s sociology of the academy, and Lefebvre’s conceptual trilogy of perceived, conceived, and lived space.

text: The gown and the korowai: Maori doctoral students and the spatial organization of academic knowledge This paper draws on 38 student interviews carried out in the course of the team research project Teaching and Learning in the Supervision of Māori Doctoral Students. Māori doctoral thesis work takes place in the intersections between the Māori (tribal) world of identifications and obligations, the organisational and epistemological configurations of academia, and the bureaucratic requirements of funding or employing bureaucracies. To explore how students accommodate cultural, academic and bureaucratic demands, we develop analytical tools combining three intellectual traditions: Māori educational theory, Bernstein’s sociology of the academy, and Lefebvre’s conceptual trilogy of perceived, conceived, and lived space.

year: 2009