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In recent years, deep learning (DL) approaches have been proven effective in addressing high nonlinear relationships within complex systems. Although various scientific studies have primarily focused on optimizing model architecture and enhancing its computational efficiency through hybridization, they have neglected the crucial aspect of selecting appropriate predictor variables (PV) and their influence on the model's predictions. In this paper, a new multi-phase stochastic DL model is designed with a feature selection framework for monthly streamflow prediction. The multi-phase hybrid MCMC–BC–BiLSTM–BiGRU model is based on bidirectional long short-term memory (BiLSTM) and bidirectional gated recurrent unit (BiGRU) integrated with Markov Chain Monte Carlo (MCMC) based bivariate copulas (BC). First, Ant Colony Optimization (ACO) algorithm was employed for screening optimal PV, and then significant antecedent streamflow was coupled with it to generate optimized input combinations. In addition, 25 different MCMC–BC models were adopted for each input combination to determine the dependency of previous month's streamflow on current and future streamflow. Finally, best-fitted MCMC–BC model was integrated with hybrid BILSTM–BiGRU model to predict streamflow at nine different catchments in the Victoria region of the Upper Murray Basin (UMB), Australia. The experimental results show that the multi-phase hybrid MCMC–BC–BiLSTM–BiGRU model showed remarkable performance in comparison to its benchmark counterparts with respect to different robust statistical error metrics. Therefore, this study demonstrates that stochastic DL techniques can be effectively employed as a promising alternative predictive tool for upstream discharge predictions with high consistency and accuracy, specifically when a statistically significant relationship with the antecedent streamflow exists. [ABSTRACT FROM AUTHOR]

Reflecting international patterns, Aboriginal people in Victoria are more likely to gamble and to experience gambling harm than non-Indigenous Victorians. This paper describes experiences of gambling reported by 50 Aboriginal people interviewed in regional Victoria in 2016 and 2017 as part of studies initiated by two Aboriginal community-controlled organisations. Data were analysed using social practice theory (SPT) and coded to the elements of 'meaning', 'material', 'competence', and 'temporality'. Across each element we identified highly contradictory experiences. Gambling held meaning as an opportunity for community gatherings but was also regarded as a cause of domestic violence, conflict, isolation and shame. Materially, the venues that offered gambling were experienced by many Aboriginal people as safe and welcoming, but at the same time gambling produced a damaging affective sense of addiction for some. Gambling was a competency that some people valued and taught to children, but it was also seen as undermining cultural practices. While Aboriginal people were historically denied access to licensed venues offering commercial gambling, many participants now found opportunities to gamble inescapable. The intermingling of benefits and harms described above supports the need for a multi-faceted response to gambling in Aboriginal communities, which includes harm reduction as well as supply restriction and treatment. Some experiences of gambling related by our participants reflected those reported also by non-Indigenous Australians, while others were differently nuanced. Because SPT is used to understand collectively-shared practices, it facilitates the identification of gambling interventions at the level of the community, as recommended by our research participants. [ABSTRACT FROM AUTHOR]

This paper reports on a study of Australian early childhood teachers' pedagogical practices with young children experiencing parental separation and divorce. Twenty-one semi-structured interviews and a focus group were conducted to explore the actions of teachers to support young children experiencing parental separation and divorce. A grounded theory approach was used to analyse data. Teachers reported actions that were focussed on constructing emotional, behavioural, and academic support for young children, as well as forming partnerships with parents, school personnel, and community members to assist. Results are discussed in terms of the implications for professional practice. [ABSTRACT FROM AUTHOR]