Theoretical Beacons: Maturana's Theory in Clinical Practice

This paper introduces several theoretical constructs drawn from the work of Humberto Maturana that can be applied to a diverse range of clinical contexts, including supervision. These constructs are: love as a fundamental need of human beings; pathways of explanation: (Objectivity), Objectivity; Emotioning; Structural Coupling; Plasticity; Domains of Operational Coherences. These constructs assist in choosing a point of entry for specific clinical situations and form a foundation on which one's preferred model of practice can be built.     

Beyond Individualised Approaches to Diabetes Type 2

Explanations for type 2 diabetes are broadened beyond the individual body and ‘bad lifestyles’ to include major institutions, the social and material contexts of food and eating, and employment. Precarious employment, a social determinant of health, encourages changes to food practices, lowers working conditions, worsens health, can bring poverty and increases shift work, a causal risk factor for diabetes. Scientists have played a part in revolutionising foods and technologies which minimise labour and movement. There are excess additives in processed food. Genetic explanations for the higher rates of diabetes in First Nations peoples give way to social explanations: colonial history, British/Euro‐American cuisine, food insecurity, trauma and social conditions resulting in chronic stress. Self‐management education takes a ‘nutritionist’ approach towards food and eating and tends to minimise the social context and skills of those with the condition particularly women workers in poorer social groups who have higher rates of diabetes (T2DM).     

Never the Twain Shall Meet: A Memetic Analysis of Poverty Perceptions

Poverty, as defined within development discourse, does not fully capture the reality in which the poor live, which is formed also by values and beliefs specific to a given culture and setting. This article uses a memetic approach to investigating the reality of poverty among pastoralists and urban dwellers in Kenya. By distinguishing the semantic space and the cultural context in which the definitions are framed, it enables the researcher to make sufficient generalisations while also recognising the differences between cultures. The results demonstrate how pastoralists and urban dwellers conceptualise poverty differently particularly in regard to causes. Further, the article suggests that development actors often utilise a Western construct which does not entirely reflect the values and beliefs of the poor.     

Rural Victorian service provider responses to the National Disability Insurance Scheme

The National Disability Insurance Scheme (NDIS) has transformed the nature of funding available to health and human service organisations to provide services to people with disability in Australia. However, there is relatively scant literature on the rural implementation of the NDIS, particularly how rural NDIS service providers are affected by the NDIS. Researchers conducted semi-structured interviews with 20 health professionals employed by rural providers, and analysed data using rural and remote health and organisational change frameworks to understand how rural providers were impacted by and responded to the NDIS. The findings suggest rural providers were impacted to differing extents and responded to the NDIS in different ways. Participants reported that disability and community health services were affected more than hospitals and private allied health practices. Impacted rural providers responded by changing the nature and types of services, service processes and their workforce, and redefining organisational characteristics. Impacted rural providers may require additional support to continue providing services, and those less impacted may require other incentives to better engage with the NDIS. Rural proofing of NDIS policy could reveal suitable supports and incentives to ensure rural people with disability can access required services.     

A machine learning analysis of drought and rural population change on the North American Great Plains since the 1970s

Population and Environment - Machine learning techniques have to date not been widely used in population-environment research, but represent a promising tool for identifying relationships between...     

Infants' First Words are not Phonetically Specified: Own Name Recognition in British English‐Learning 5‐Month‐Olds

By the end of their first year of life, infants’ representations of familiar words contain phonetic detail; yet little is known about the nature of these representations at the very beginning of word learning. Bouchon et al. ( 2015 ) showed that French‐learning 5‐month‐olds could detect a vowel change in their own name and not a consonant change, but also that infants reacted to the acoustic distance between vowels. Here, we tested British English‐learning 5‐month‐olds in a similar study to examine whether the acoustic/phonological characteristics of the native language shape the nature of the acoustic/phonetic cues that infants pay attention to. In the first experiment, British English‐learning infants failed to recognize their own name compared to a mispronunciation of initial consonant (e.g., Molly versus Nolly) or vowel (e.g., April versus Ipril). Yet in the second experiment, they did so when the contrasted name was phonetically dissimilar (e.g., Sophie versus Amber). Differences in phoneme category (stops versus continuants) between the correct consonant versus the incorrect one significantly predicted infants’ own name recognition in the first experiment. Altogether, these data suggest that infants might enter into a phonetic mode of processing through different paths depending on the acoustic characteristics of their native language.     

R2 Bounds for Predictive Models: What Univariate Properties Tell us About Multivariate Predictability

ABSTRACT

A long-standing puzzle in macroeconomic forecasting has been that a wide variety of multivariate models have struggled to out-predict univariate models consistently. We seek an explanation for this puzzle in terms of population properties. We derive bounds for the predictive R² of the true, but unknown, multivariate model from univariate ARMA parameters alone. These bounds can be quite tight, implying little forecasting gain even if we knew the true multivariate model. We illustrate using CPI inflation data. Supplementary materials for this article are available online.