There are two fundamentally different kinds of comparison: DIFFERENCE comparisons and CONTRAST comparisons. Unlike adjective phrases, noun phrases can occur in contrast comparisons (such as This bird is more a duck than a goose), but not in difference comparisons (#This bird is more a duck than that one is), where the mediation of a partitive particle is necessary (as in more of a duck). The problem is that postulating either semantic gradability or even just ad-hoc, metalinguistic, gradable interpretations for nouns in order to capture the meaning of contrast comparisons results in wrong predictions for difference comparisons and for most other gradable constructions (#very duck, #too duck, #duck enough, #the most duck). This article presents an account that exploits the psychological notion of a CONTRAST SET to explain these data and to correctly predict the truth conditions and characteristic inference patterns of contrast comparisons. Two main conclusions are, first, that if adjectives are degree expressions, so are nouns, and second, that nouns form a different type of degree expression.

A certain class of English adjectives known as a-adjectives resist appearing attributively as prenominal modifiers (e.g. ??the afraid boy, ??the asleep man). Boyd & Goldberg 2011 had offered experimental evidence suggesting that the dispreference is learnable on the basis of categorization and STATISTICAL PREEMPTION: repeatedly witnessing predicative formulations in contexts in which the attributive form would otherwise be appropriate. The present reply addresses Yang's (2015) counterproposal for how a-adjectives are learned and his instructive critique of statistical preemption. The counterproposal is that children receive evidence that a-adjectives behave like locative particles in occurring with certain adverbs such as far and right. However, in an analysis of the 450-million-word COCA corpus, the suggested adverbial evidence is virtually nonexistent (e.g. *far alive, * straight afraid). In fact, these adverbs occur much more frequently with typical adjectives (e.g. far greater, straight alphabetical). Furthermore, relating a-adjectives to locative particles does not provide evidence of the restriction, because locative particles themselves can appear as prenominal modifiers (the down payment, the outside world). The critique of statistical preemption is based on a 4.3-million-word corpus analysis of child-directed speech that suggests that children cannot amass the requisite evidence before they are three years old. While we clarify which sorts of data are relevant to statistical preemption, we concur that the required data is relatively sparsely represented in the input. In fact, recent evidence suggests that children are not actually cognizant of the restriction until they are roughly ten years old, an indication that input of an order of magnitude more than 4.3 million words may be required. We conclude that a combination of categorization and statistical preemption is consistent with the available evidence of how the restriction on a-adjectives is learned.

This article examines how the International Labour Office (ILO) tried to disseminate one of its statistical tools, the International Standard Classification of Occupations (ISCO), in sub-Saharan Africa, in the context of decolonization and development planning. It sheds light on the changing relations in the late 1950s and early 1960s between the ILO, late colonial and then national administrations, and a regional organization, the Combined Commission for Technical Cooperation in Africa South of the Sahara (CCTA). Although characterized by rivalry, misunderstandings, and sometimes indifference, these relations were also marked by partially overlapping interests. Focusing on the successive ILO experts responsible for developing occupational classifications, this paper shows how their interactions with local actors reshaped the project which they had to carry out. For instance, it gave a greater place to the training of national civil servants or contributed to the realization of the 1962 Nigerian census. In particular, the article analyzes the connections made with other international programs (relating to demography and economic planning) on the ground, and the resulting interdependence among them. By doing so, the ILO expert responsible for the project on occupational classifications benefited from the resources of other technical assistance programs and tried to demonstrate to national authorities the importance of the project which could apply in various fields. While unexpected difficulties limited the scope of the initial project to Nigeria alone, the paper discusses how ILO officials inscribed occupational classifications in the general framework of development planning.

Categorization is a dynamic cognitive process that organizes human knowledge. As such, categorization processes are integral of the linguistic system and are primarily manifested in the conceptual categories represented in semantic memory. Linguistic theory has proposed various models to describe the nature and structure of semantic categories. This paper reviews the traditional definitions of four types of linguistic categories (natural or taxonomic, ad hoc, radial and scripts) from the complex network paradigm. The semantic networks have been constructed from a semantic fluency task (Animals, Objects laid on the table, Games and Countryside) involving 680 native Spanish speakers. Both the structure of the network and its dynamics are analysed, remarking the process by which speakers create the network through their linguistic performance. For this purpose, traditional mathematical measures from network theory were employed, and new measures were proposed to more precisely distinguish between the four types of categories. The results support the principles of linguistic description, expanding and refining the properties of the different types of semantic categories. Furthermore, they highlight the importance of fine-grained modularity measures as key to interpreting differences in conceptual categories.

This paper reports an experiment using Stag Hunt games with different payoff ranges. Specifically, in one treatment for half of the games the payoff dominant and the risk dominant equilibrium coincide and for the other half of the games they conflict; in the second treatment they always conflict. The experiment provides evidence that the payoff range experienced by the participant influences the likelihood of efficient conventions emerging. In particular, experiencing games where payoff dominance and risk dominance coincide appears to make payoff dominance more attractive in games in which they conflict. In the experiment, we also observe conditional behavior emerging with experience. We develop a model of conditional expectations to explain these stylized facts that depends crucially on the assumption that after a brief learning period participants categorize their experience using the same relative bandwidth in both treatments even though the range of experience is twice as large in treatment 1 as it is in treatment 2. The assumption cannot be rejected by the data. The analysis provides a formal example in which increasing experienced diversity by changing the way similar experiences are categorized increases the likelihood of efficient conventions emerging in communities playing similar Stag Hunt games.

Experimental game theory studies the behavior of agents who face a stream of one-shot games as a form of learning. Most literature focuses on a single recurring identical game. This paper embeds single-game learning in a broader perspective, where learning can take place across similar games. We posit that agents categorize games into a few classes and tend to play the same action within a class. The agent’s categories are generated by combining game features (payoffs) and individual motives. An individual categorization is experience-based, and may change over time. We demonstrate our approach by testing a robust (parameter-free) model over a large body of independent experimental evidence over $2\times 2$ symmetric games. The model provides a very good fit across games, performing remarkably better than standard learning models.

We introduce a new statistical procedure for the identification of unobserved categories that vary between individuals and in which objects may span multiple categories. This procedure can be used to analyze data from a proposed sorting task in which individuals may simultaneously assign objects to multiple piles. The results of a synthetic example and a consumer psychology study involving categories of restaurant brands illustrate how the application of the proposed methodology to the new sorting task can account for a variety of categorization phenomena including multiple category memberships and for heterogeneity through individual differences in the saliency of latent category structures.

The p-median offers an alternative to centroid-based clustering algorithms for identifying unobserved categories. However, existing p-median formulations typically require data aggregation into a single proximity matrix, resulting in masked respondent heterogeneity. A proposed three-way formulation of the p-median problem explicitly considers heterogeneity by identifying groups of individual respondents that perceive similar category structures. Three proposed heuristics for the heterogeneous p-median (HPM) are developed and then illustrated in a consumer psychology context using a sample of undergraduate students who performed a sorting task of major U.S. retailers, as well as a through Monte Carlo analysis.

Categorization plays a crucial role in organizing experiences, allowing us to make sense of the world. This process is reflected in the labels speakers use for geographical areas. This study investigates the categorization of geographical areas reflected in phrases including nouns for the three Swedish regions of Norrland, Svealand, or Götaland, and the conjunction och (‘and’). Using data from the Swedish Korp corpus (Borin et al. 2012), we examine how these regions and areas within them are represented in governmental, news, and social media texts. Results show that Svealand and Götaland are more commonly used with nouns for regions than Norrland. Norrland is used with phrases for more specific locations within the other regions (e.g. their towns and provinces) but also considerably larger areas (e.g. countries and continents) more commonly than the other regions, revealing asymmetry in how geographical areas in Sweden are categorized.

This research probed how classifiers marking an object’s membership in the grammar of classifier languages like Mandarin Chinese and Korean may influence their speakers to categorize objects differently compared to speakers of non-classifier languages like English. Surveys in multiple-choice format were given to native speakers of the three languages. Analysis of the results demonstrated that significant proportions of Mandarin Chinese and Korean speakers behaved differently from English speakers due to the classifier-based strategy influencing classifier language speakers’ categorization. Adopting the Competition Model, we suggest that among the various categorizing strategies available to language users, the one with the greatest strength at the moment of performing the task wins the categorization competition. Classifiers that are grammaticalized in classifier languages may be providing their speakers with a powerful cognitive tool to notice diverse characteristics shared between objects, which is usually unavailable to non-classifier languages. Therefore, the strength of classifier-based strategy in the minds of classifier language speakers is strong enough to win some of the categorization competitions, which guides them to make different categorizing decisions from non-classifier language users.

We argue that a taken-for-granted category gives way to a new category when strategic behavior becomes stigmatized. As a result, even bystander firms that have engaged in similar strategic behavior, such as lobbying, will be penalized by their association with the culpable strategic behavior. The extent of their association with the culpable behavior will determine the level of punishment they receive. However, if a trustworthy third party administers a corrective measure, the affected firms can regain their lost legitimacy. The extent of their restoration is proportional to the amount of legitimacy that was lost. We provide empirical evidence for this argument by analyzing the Jack Abramoff case, one of the most notorious corrupt lobbying cases in US history. We find that bystander firms were penalized by shareholders when the corrupt lobbying was revealed. Furthermore, the penalty was more severe for bystander firms that engaged in more lobbying activities and hired more revolving-door lobbyists. We also find that the subsequent legal remedy helped the bystander firms that were penalized the most to recover the most from their losses. We confirm the theoretical notion using the Enron case as well.