The proliferation of news and information sources has motivated a need to identify those providing legitimate journalism. One temptation is to go the route of such fields as medicine and law, namely to formally professionalize. This gives a clear method for determining who is a member, with an array of associated responsibilities and rewards. We argue that making such a formal move in journalism is a mistake: Journalism does not meet the traditional criteria, and its core ethos is in conflict (...) with the professional mindset. We thus shift the focus from whether the person is journalist to whether the work satisfies the conditions that characterize legitimate journalism. In explaining those conditions we also look at mechanisms for enhancing the power of persons doing journalism, drawing upon lessons from the labor movement. We also consider a self-declaration model while urging increased literacy from all participants in the news gathering and consuming enterprise. (shrink)
Mitchell et al. contemplate the possibility of rats being capable of propositional reasoning. We suggest that this is an unlikely and unsubstantiated possibility. Nonhuman animals and human infants do learn about the contingencies in the world; however, such learning seems not to be based on propositional reasoning, but on more elementary associative processes.
Theories of how organisms learn about cause-effect relations have a history dating back at least to the associationist/mechanistic hypothesis of David Hume. Some contemporary theories of causal learning are descendants of Hume's mechanistic models of conditioning, but others impute principled, rule-based reasoning. Since even primitive animals are conditionable, it is clear that there are built-in mechanical algorithms that respond to cause/effect relations. The evidence suggests that humans retain the use of such algorithms, which are surely adaptive when causal judgments must (...) be rapidly made. But we know very little about what these algorithms are and about when and with what ratiocinative procedures they are sometimes replaced. Nor do we know how the concept of causation originates in humans. To clarify some of these issues, this paper surveys the literature and explores the behavioral predictions made by two contrasting theories of causal learning: the mechanical Rescorla-Wagner model and the sophisticated reasoning codified in Bayes' Theorem. (shrink)
Hoerl & McCormack propose that animals learn sequences through an entrainment-like process, rather than tracking the temporal addresses of each event in a given sequence. However, past research suggests that animals form “temporal maps” of sequential events and also comprehend the concept of ordinal position. These findings suggest that a clarification or qualification of the authors’ hypothesis is needed.
In documenting the dizzying diversity of human languages, Evans & Levinson (E&L) highlight the lack of universals. This suggests the need for complex learning. Yet, just as there is no universal structure, there may be no universal learning mechanism responsible for language. Language is a behavior assembled by many processes, an assembly guided by the language being learned.
thought, in general, and – reasoning by analogy, in particular, have been said to reside at the very summit of human cognition. Leech et al. endeavor to comprehend the development of analogous thinking in human beings. Applying Leech et al.'s general approach to the evolution of analogical behavior in animals might also prove to be of considerable value.
The history of comparative psychology is replete with proclamations of human uniqueness. Locke and Morgan denied animals relational thought; Darwin opened the door to that possibility. Penn et al. may be too quick to dismiss the cognitive competences of animals. The developmental precursors to relational thought in humans are not yet known; providing animals those prerequisite experiences may promote more advanced relational thought.