title: "Be feared, or live in fear": A descriptive model of institutional gang violence

authors: Brennan-Tupara, Nicola Dawn

subjects: Gang

abstract: Prison violence is a significant concern both in New Zealand and across the globe. While past theories and empirical research have highlighted several risk factors implicated in prison violence, we continue to have a limited understanding of what happens, and why it happens, during a prison violence event (PVE). Furthermore, we have even less of an understanding about the involvement of gangs in prison violence despite research suggesting that gang members are over-represented when it comes to involvement in such incidents. Previous research on gang violence in prison also focuses heavily on prisons in the United States of America which have different cultural, social, and judicial dimensions and may not generalise to the New Zealand prison population. This research project aimed to fill some of these gaps by taking an exploratory approach to induce new ideas following interviews with gang members who have first-hand experience with perpetrating prison violence. We used Grounded Theory to collect and analyse event descriptions to build a descriptive model of institutional gang violence which describes the distal and proximal features of the PVE process. The resulting model contributes to a better understanding of the function of PVEs involving gang members and the extent to which these events differ when carried out for or on behalf of the gang. It also highlights the role of past trauma and the prison ecology in the perpetuation of these events.

text: "Be feared, or live in fear": A descriptive model of institutional gang violence Prison violence is a significant concern both in New Zealand and across the globe. While past theories and empirical research have highlighted several risk factors implicated in prison violence, we continue to have a limited understanding of what happens, and why it happens, during a prison violence event (PVE). Furthermore, we have even less of an understanding about the involvement of gangs in prison violence despite research suggesting that gang members are over-represented when it comes to involvement in such incidents. Previous research on gang violence in prison also focuses heavily on prisons in the United States of America which have different cultural, social, and judicial dimensions and may not generalise to the New Zealand prison population. This research project aimed to fill some of these gaps by taking an exploratory approach to induce new ideas following interviews with gang members who have first-hand experience with perpetrating prison violence. We used Grounded Theory to collect and analyse event descriptions to build a descriptive model of institutional gang violence which describes the distal and proximal features of the PVE process. The resulting model contributes to a better understanding of the function of PVEs involving gang members and the extent to which these events differ when carried out for or on behalf of the gang. It also highlights the role of past trauma and the prison ecology in the perpetuation of these events.

year: 2023

title: Random model trees: an effective and scalable regression method

authors: Pfahringer, Bernhard

subjects: computer science

abstract: We present and investigate ensembles of randomized model trees as a novel regression method. Such ensembles combine the scalability of tree-based methods with predictive performance rivaling the state of the art in numeric prediction. An extensive empirical investigation shows that Random Model Trees produce predictive performance which is competitive with state-of-the-art methods like Gaussian Processes Regression or Additive Groves of Regression Trees. The training
and optimization of Random Model Trees scales better than Gaussian Processes Regression to larger datasets, and enjoys a constant advantage over Additive Groves of the order of one to two orders of magnitude.

text: Random model trees: an effective and scalable regression method We present and investigate ensembles of randomized model trees as a novel regression method. Such ensembles combine the scalability of tree-based methods with predictive performance rivaling the state of the art in numeric prediction. An extensive empirical investigation shows that Random Model Trees produce predictive performance which is competitive with state-of-the-art methods like Gaussian Processes Regression or Additive Groves of Regression Trees. The training
and optimization of Random Model Trees scales better than Gaussian Processes Regression to larger datasets, and enjoys a constant advantage over Additive Groves of the order of one to two orders of magnitude.

year: 2010-06

title: The science-society relationship in Aotearoa: practicing responsible innovation in the New Zealand research and innovation system

authors: Finlay-Smits, Susanna

subjects: Responsible innovation

abstract: Reports on Aotearoa New Zealand’s research, science, and innovation (RSI) system suggest the sector could improve its social responsibility and create more social value. However, researchers and innovators within the sector find this challenging. Through qualitative interviews and a national survey of RSI system participants, this study explores the current perceptions, practices enacted, and support given around responsible research and innovation practices. Findings indicate that researchers and innovators have diverse understandings of what responsible research and innovation entails, viewing anticipation and reflexivity-aligned practices as the most important aspects of responsible research and innovation. Participants feel most supported by research organisations and funding bodies to enact such aspects of responsible practice. However, they perceive a discrepancy, across all dimensions explored, between what researchers and innovators should do, and what they actually do in terms of enacting responsible practices. Thus, significant room for improvement is identified, particularly regarding practices that align with researchers’ and innovators’ obligations under Te Tiriti o Waitangi, and requirements under Vision Mātauranga.

text: The science-society relationship in Aotearoa: practicing responsible innovation in the New Zealand research and innovation system Reports on Aotearoa New Zealand’s research, science, and innovation (RSI) system suggest the sector could improve its social responsibility and create more social value. However, researchers and innovators within the sector find this challenging. Through qualitative interviews and a national survey of RSI system participants, this study explores the current perceptions, practices enacted, and support given around responsible research and innovation practices. Findings indicate that researchers and innovators have diverse understandings of what responsible research and innovation entails, viewing anticipation and reflexivity-aligned practices as the most important aspects of responsible research and innovation. Participants feel most supported by research organisations and funding bodies to enact such aspects of responsible practice. However, they perceive a discrepancy, across all dimensions explored, between what researchers and innovators should do, and what they actually do in terms of enacting responsible practices. Thus, significant room for improvement is identified, particularly regarding practices that align with researchers’ and innovators’ obligations under Te Tiriti o Waitangi, and requirements under Vision Mātauranga.

year: 2023-05-17