Returns to Foreign Language Skills in a Developing Country: The Case of Turkey

Foreign language skills represent a form of human capital that can be rewarded in the labor market. Drawing on data from the Adult Education Survey of 2007, this is the first study estimating returns to foreign language skills in Turkey. We contribute to the literature on the economic value of language knowledge, with a special focus on a country characterized by fast economic and social development. Although English is the most widely spoken foreign language in Turkey, we initially consider the economic value of different foreign languages among the employed males aged 25 to 65. We find positive and significant returns to proficiency in English and Russian, which increase with the level of competence. Knowledge of French and German also appears to be positively rewarded in the Turkish labor market, although their economic value seems mostly linked to an increased likelihood to hold specific occupations rather than increased earnings within occupations. Focusing on English, we also explore the heterogeneity in returns to different levels of proficiency by frequency of English use at work, birth-cohort, education, occupation and rural/urban location. The results are also robust to the endogenous specification of English language skills.

Lengua familiar y conocimiento de la lengua escolar en Cataluña al finalizar la Educación Infantil = Home Language and Knowledge of the School Language in Catalonia at the end of Nursery School

La infancia extranjera se escolariza en Cataluña en un programa de cambio de lengua del hogar a la escuela. Las investigaciones afirman que este alumnado tarda un mínimo de seis años en equiparar sus habilidades lingüístico-cognitivas con sus pares autóctonos, no así las habilidades conversacionales, las cuales se adquieren antes de los dos años de residencia. Sin embargo, no existen estudios sobre los efectos de la escolarización en el parvulario del alumnado alófono, así como de su lengua familiar, en relación con la adquisición de la lengua escolar. El artículo es un estudio comparativo de la adquisición del catalán de 567 autóctonos y 434 alófonos, al final del parvulario, en 50 escuelas de Cataluña que escolarizan a alumnado de origen extranjero. Las lenguas del alumnado autóctono son el catalán, el castellano y el bilingüismo catalán-castellano y las lenguas del alumnado alófono son el árabe, el soninké y el castellano. Los factores utilizados más relevantes han sido el nivel socioprofesional y educativo de las familias, el tiempo de residencia y el momento de escolarización del alumnado, el porcentaje de alumnado catalanohablante y de alumnado alófono en el aula y el contexto sociolingüístico del centro escolar. Los resultados muestran que el alumnado autóctono sabe más catalán que el alumnado alófono, pero las diferencias desaparecen respecto a algunos factores, de los cuales los más relevantes son los relacionados con las características del alumnado de las aulas. La lengua familiar del alumnado alófono no incide en sus resultados

Emotion, Affect, Sentiment: The Language and Aesthetics of Feeling

Bringing together experts from linguistics, medieval and modern literary studies, this volume offers a transhistorical look at the language and cultural work of emotion in a variety of written, oral and visual texts. Contributors engage with the recent so-called affective turn, but also examine the language and use of emotion from a variety of perspectives, touching on issues such as Romantic and Modernist aesthetics, the history of emotions, melodramatic and the Gothic, reception aesthetics, rudeness, and medicine.

Apprentissage automatique de la morphologie : le cas des structures racine-schème

RÉSUMÉ Cette thèse porte sur le développement de méthodes algorithmiques pour découvrir automatiquement la structure morphologique des mots d'un corpus. On considère en particulier le cas des langues s'approchant du type introflexionnel, comme l'arabe ou l'hébreu. La tradition linguistique décrit la morphologie de ces langues en termes d'unités discontinues : les racines consonantiques et les schèmes vocaliques. Ce genre de structure constitue un défi pour les systèmes actuels d'apprentissage automatique, qui opèrent généralement avec des unités continues. La stratégie adoptée ici consiste à traiter le problème comme une séquence de deux sous-problèmes. Le premier est d'ordre phonologique : il s'agit de diviser les symboles (phonèmes, lettres) du corpus en deux groupes correspondant autant que possible aux consonnes et voyelles phonétiques. Le second est de nature morphologique et repose sur les résultats du premier : il s'agit d'établir l'inventaire des racines et schèmes du corpus et de déterminer leurs règles de combinaison. On examine la portée et les limites d'une approche basée sur deux hypothèses : (i) la distinction entre consonnes et voyelles peut être inférée sur la base de leur tendance à alterner dans la chaîne parlée; (ii) les racines et les schèmes peuvent être identifiés respectivement aux séquences de consonnes et voyelles découvertes précédemment. L'algorithme proposé utilise une méthode purement distributionnelle pour partitionner les symboles du corpus. Puis il applique des principes analogiques pour identifier un ensemble de candidats sérieux au titre de racine ou de schème, et pour élargir progressivement cet ensemble. Cette extension est soumise à une procédure d'évaluation basée sur le principe de la longueur de description minimale, dans- l'esprit de LINGUISTICA (Goldsmith, 2001). L'algorithme est implémenté sous la forme d'un programme informatique nommé ARABICA, et évalué sur un corpus de noms arabes, du point de vue de sa capacité à décrire le système du pluriel. Cette étude montre que des structures linguistiques complexes peuvent être découvertes en ne faisant qu'un minimum d'hypothèses a priori sur les phénomènes considérés. Elle illustre la synergie possible entre des mécanismes d'apprentissage portant sur des niveaux de description linguistique distincts, et cherche à déterminer quand et pourquoi cette coopération échoue. Elle conclut que la tension entre l'universalité de la distinction consonnes-voyelles et la spécificité de la structuration racine-schème est cruciale pour expliquer les forces et les faiblesses d'une telle approche. ABSTRACT This dissertation is concerned with the development of algorithmic methods for the unsupervised learning of natural language morphology, using a symbolically transcribed wordlist. It focuses on the case of languages approaching the introflectional type, such as Arabic or Hebrew. The morphology of such languages is traditionally described in terms of discontinuous units: consonantal roots and vocalic patterns. Inferring this kind of structure is a challenging task for current unsupervised learning systems, which generally operate with continuous units. In this study, the problem of learning root-and-pattern morphology is divided into a phonological and a morphological subproblem. The phonological component of the analysis seeks to partition the symbols of a corpus (phonemes, letters) into two subsets that correspond well with the phonetic definition of consonants and vowels; building around this result, the morphological component attempts to establish the list of roots and patterns in the corpus, and to infer the rules that govern their combinations. We assess the extent to which this can be done on the basis of two hypotheses: (i) the distinction between consonants and vowels can be learned by observing their tendency to alternate in speech; (ii) roots and patterns can be identified as sequences of the previously discovered consonants and vowels respectively. The proposed algorithm uses a purely distributional method for partitioning symbols. Then it applies analogical principles to identify a preliminary set of reliable roots and patterns, and gradually enlarge it. This extension process is guided by an evaluation procedure based on the minimum description length principle, in line with the approach to morphological learning embodied in LINGUISTICA (Goldsmith, 2001). The algorithm is implemented as a computer program named ARABICA; it is evaluated with regard to its ability to account for the system of plural formation in a corpus of Arabic nouns. This thesis shows that complex linguistic structures can be discovered without recourse to a rich set of a priori hypotheses about the phenomena under consideration. It illustrates the possible synergy between learning mechanisms operating at distinct levels of linguistic description, and attempts to determine where and why such a cooperation fails. It concludes that the tension between the universality of the consonant-vowel distinction and the specificity of root-and-pattern structure is crucial for understanding the advantages and weaknesses of this approach.

Psychometrics of the Dyadic Coping Inventory in three language groups

This article introduces the Dyadic Coping Inventory (DCI; Bodenmann, 2008) and aims (1) to investigate the reliability and aspects of the validity of the Italian and French versions of the DCI, and (2) to replicate its factor structure and reliabilities using a new Swiss German sample. Based on 216 German-, 378 Italian-, and 198 French-speaking participants, the factor structure of the original German inventory was able to be replicated by using principal components analysis in all three groups after excluding two items in the Italian and French versions. The latter were shown to be as reliable as the German version with the exception of the low reliabilities of negative dyadic coping in the French group. Confirmatory factor analyses provided additional support for delegated dyadic coping and evaluation of dyadic coping. Intercorrelations among scales were similar across all three languages groups with a few exceptions. Previous findings could be replicated in all three groups, showing that aspects of dyadic coping were more strongly related to marital quality than to dyadic communication. The use of the dyadic coping scales in the actor-partner interdependence model, the common fate model, and the mutual influence model is discussed.

Well, you have hepatic metastases: Use of technical language by medical students in simulated patient interviews.

OBJECTIVE: This research explored medical students' use and perception of technical language in a practical training setting to enhance skills in breaking bad news in oncology. METHODS: Terms potentially confusing to laypeople were selected from 108 videotaped interviews conducted in an undergraduate Communication Skills Training. A subset of these terms was included in a questionnaire completed by students (N=111) with the aim of gaining insight into their perceptions of different speech registers and of patient understanding. Excerpts of interviews were analyzed qualitatively to investigate students' communication strategies with respect to these technical terms. RESULTS: Fewer than half of the terms were clarified. Students checked for simulated patients' understanding of the terms palliative and metastasis/to metastasize in 22-23% of the interviews. The term ambulatory was spontaneously explained in 75% of the interviews, hepatic and metastasis/to metastasize in 22-24%. Most provided explanations were in plain language; metastasis/to metastasize and ganglion/ganglionic were among terms most frequently explained in technical language. CONCLUSION: A significant number of terms potentially unfamiliar and confusing to patients remained unclarified in training interviews conducted by senior medical students, even when they perceived the terms as technical. PRACTICE IMPLICATIONS: This exploration may offer important insights for improving future physicians' skills.