450 research outputs found

    Segmenting excessive alcohol consumers : implications for social marketing

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    While extant studies have mainly investigated differences between drinkers and non-drinkers, the literature on segmenting heavy drinkers and profiling them is surprisingly scarce. This study makes a significant contribution to the social marketing literature by illustrating a novel way of targeting heavy drinkers by utilizing their health management styles and provides useful insights into understanding how segmentation could be a valuable tool for developing effective social marketing programmes that are aimed at reducing excessive alcohol consumption. Analysis of data collected through the HINTS study reveals a two-cluster segmentation model. The two segments of heavy drinkers distinctly differ in terms of the extent of reliance and trust they place on health service professionals. Hence, the segmentation analysis provides interesting and novel insights into the level of dependence of heavy drinkers on the health care system and their health management styles. The study provides an actionable perspective for future research, public policy and social marketing

    Dryland pasture legume programme

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    1. Medic variety evaluation a. Row Evaluation - 88ME122 - Merredin. This method of assessment was used to test a range of new medic material originating from the South Australian Department of Agriculture. b. Evaluation of burr medics on Morrel soils. - 88ME84 - Nokaning. c. Evaluation of burr medics on Whitegum soils. 88ME85 - North Kellerberrin. d. Evaluation of Santiago in low rainfall areas - 88ME86 - Mukinbudin. e. Selection of early maturing M. murex. 88SC30 - Merredin. f. Medic species evaluation - large plots. 88NO88 - Tammin. g. Medic species evaluation - large plots. 85M43 - Merredin Research Station. h. Medic species defoliation trial - 84LG34 - North East Pingrup. i. Medic variety evaluation - large plots 87M73 - Merredin Research Station. j. M. polymorpha variety evaluation - large plots. 86M65 - Merredin Research Station. k. Medic variety evaluation - large plots. 85ME49 - Kellerberrin. 2. Serradella Variety Evaluation. a. Large machine sown plots - new sowings. 88ME88 - Woolocutty. b. Evaluation of serradella on acid sandplain soils. 88ME90, 88ME92 - South Burracoppin. c. Saradella variety trial. 87M62 - South Carrabin annexe. d. Rate and depth of sowing of Serradella. 87M63 - South Carrabin annexe. 3. Pasture Agronomy a. Establishing burr medic pastures with cereal cover crops. 88M56 - Merredin Research Station b. Response of medic pasture to gypsum application. 88ME79 - North Bodallin. c. Effect of sulphur on medic growth - pot trial. 87M91 - Glasshouse, Merredin Research Station. d. Control of doublegees in medic pasture. 88ME93 - North Kellerberrin. e. Establishing Serradella under a cereal crop. 87M64 - South Carrabin annexe. f. Management of Serradella pastures. 87M92 - South Carrabin annexe. g. Broadleaf herbicide tolerance of Serradella. 88ME94 - North Kellerberin. h. Control of capeweed and turnip in Serradella pastures. 88M63 - South Carrabin annexe. 4. Rotational Experiments. a. Sub. clover rotation trial. 82M47 - Merredin Research Station. b. Maintenance of sub.clover in 1:1 rotations. 82WH39 - Wongan Hills Research Station. c. Rotational systems for burr medic. 88ME83 - Merredin. d. Serena grazing trial - Newdegate Research Station

    Comparison of Gibberellins in Normal and Slender Barley Seedlings

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    The Search for Invariance: Repeated Positive Testing Serves the Goals of Causal Learning

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    Positive testing is characteristic of exploratory behavior, yet it seems to be at odds with the aim of information seeking. After all, repeated demonstrations of one’s current hypothesis often produce the same evidence and fail to distinguish it from potential alternatives. Research on the development of scientific reasoning and adult rule learning have both documented and attempted to explain this behavior. The current chapter reviews this prior work and introduces a novel theoretical account—the Search for Invariance (SI) hypothesis—which suggests that producing multiple positive examples serves the goals of causal learning. This hypothesis draws on the interventionist framework of causal reasoning, which suggests that causal learners are concerned with the invariance of candidate hypotheses. In a probabilistic and interdependent causal world, our primary goal is to determine whether, and in what contexts, our causal hypotheses provide accurate foundations for inference and intervention—not to disconfirm their alternatives. By recognizing the central role of invariance in causal learning, the phenomenon of positive testing may be reinterpreted as a rational information-seeking strategy
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