/**
* Called when a null model is about to be retrieved in order to allow a subclass to provide an
* initial model.
* <p>
* By default this implementation looks components in the parent chain owning a
* {@link IComponentInheritedModel} to provide a model for this component via
* {@link IComponentInheritedModel#wrapOnInheritance(Component)}.
* <p>
* For example a {@link FormComponent} has the opportunity to instantiate a model on the fly
* using its {@code id} and the containing {@link Form}'s model, if the form holds a
* {@link CompoundPropertyModel}.
*
* @return The model
*/
protected IModel<?> initModel()
{
IModel<?> foundModel = null;
// Search parents for IComponentInheritedModel (i.e. CompoundPropertyModel)
for (Component current = getParent(); current != null; current = current.getParent())
{
// Get model
// Don't call the getModel() that could initialize many in between
// completely useless models.
// IModel model = current.getDefaultModel();
IModel<?> model = current.getModelImpl();
if (model instanceof IWrapModel && !(model instanceof IComponentInheritedModel))
{
model = ((IWrapModel<?>)model).getWrappedModel();
}
if (model instanceof IComponentInheritedModel)
{
// return the shared inherited
foundModel = ((IComponentInheritedModel<?>)model).wrapOnInheritance(this);
setFlag(FLAG_INHERITABLE_MODEL, true);
break;
}
}
// No model for this component!
return foundModel;
}
Guided by the risk information-seeking and processing model, this study examines positive and negative affect separately in their influence on information-seeking intentions and avoidance through structural equation analyses. The highlight is that information avoidance seems to be driven by positive affect, while information seeking seems to be more heavily influenced by negative affect. Another interesting finding is that informational subjective norms are positively related to both seeking and avoidance, which suggests that one’s social environment has the potential to strongly influence the way he or she handles climate change information. Implications for theory and practice are discussed.
Welcome to the world of evidence! Evidence-based teaching is effective teaching, and we bring you the most effective methods. Read on to find out more.
J. Hausmann, and S. Kent. SoftVis '03: Proceedings of the 2003 ACM symposium on Software visualization, page 169--178. New York, NY, USA, ACM Press, (2003)
J. Hausmann, and S. Kent. SoftVis '03: Proceedings of the 2003 ACM symposium on Software visualization, page 169--178. New York, NY, USA, ACM Press, (2003)
I. Cadez, D. Heckerman, C. Meek, P. Smyth, and S. White. Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, page 280--284. ACM, (2000)