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3D"Cuadro<= o:p>

 

 

 

 

 

La Dominancia Lingüística: Causa y Consecuencia de la Manifestación de la Identidad Cultural en Context= os Multilingües. El Caso de Cataluña

 

Linguistic Dominance: Cause and Consequence of the Manifestation of Cultural Identity = in Multilingual Contexts. The Case of Catalonia

 

 

Beatriz Magalhaes-Teixeira<= /b>

Universitat de Lleida 

bmt4@alumnes.udl= .cat

 

Fernando Senar

Universitat de Lleida

fernando.senar@u= dl.cat

 

Angélica Jardim

Universitat de Lleida  <= /i>

ajb7@alumnes.udl.cat

 

Anna Amadó

Universitat de Lleida  <= /i>

anna.amado@udl.cat<= /span>

 

<= o:p> 

R= ESUMEN

El presente estudio trata de analizar= la relación que existe entre los diferentes componentes de la dominancia lingüística (usos lingüísticos, actitudes lingüísticas y competencia autopercibida) y la identidad cultural que desarrollan los individuos en Cataluña. = Se empleó una muestra de 393 participantes, los cuales fueron categoriz= ados en función de su identidad cultural y, mediante análisis ANCO= VA se compararon los grupos en función de los diferentes componentes de dominancia lingüística. Los resultados sugieren que los tres componentes de la dominancia lingüística están condicion= ados por la identidad cultural, siendo particularmente notable el elemento actitudinal. Estos resultados ayudan a explicar cómo la dominancia l= ingüística puede actuar como herramienta de reafirmación y expresión de = la identidad cultural en aquellos contextos en los que coexisten más de= una lengua y cultura como es el caso de Cataluña.

 

Palabras clav= e: Identidad cultural, Usos lingü&= iacute;sticos, Competencia autopercibida<= /span>, Actitudes lingüístic= as, Dominancia lingü&iacu= te;stica

 

 

ABSTRACT

The present study aims to analyze the relationship between different components of linguistic dominance (linguistic uses, linguistic attitudes, = and self-perceived competence) and the cultural identity developed by individua= ls in Catalonia. A sample of 393 participants was used, who were categorized according to their cultural identity. Using ANCOVA analyses, the groups were compared based on the different components of linguistic dominance. The res= ults suggest that all three components of linguistic dominance are influenced by cultural identity, with the attitudinal component being particularly notabl= e. These results help to explain how linguistic dominance can act as a tool for reaffirmation and expression of cultural identity in contexts where more th= an one language and culture coexist, as is the case in Catalonia.

Keywords: Cultural identity, Language uses, Self-perceived proficien= cy, Language attitudes, Language dominance.

 

 

1.   INTRODUCCIÓN

La relación entre la identidad cultural y el lenguaje ha sido un elemento de interés en el campo de= la psicología y la sociología. El creciente contacto intercultur= al y multilingüe ha traído muchos cambios psicológicos en la construcción de identidad de los individuos. En este contexto, la le= ngua no solo es entendida como un medio de comunicación, sino que también es percibida como una herramienta útil para la constr= ucción y expresión de la identidad cultural. En consecuencia, resulta suger= ente pensar que la dominancia lingüística y la forma en la que los individuos se identifican culturalmente están relacionados.

La identidad cultural es entendida co= mo el grado en el que las personas de una cultura determinada reconocen y se identifican con el conjunto de elementos que diferencian unas culturas de o= tras (Clark, 1990). Son numerosos los estudios que sugieren que la dominancia y/o uso lingüístico podría actuar como estrategia de reafirmación hacia una identidad cultural determinada (Grosjean, 2015; Schroeder y Marian, 2017; Siebenhütter, 2023). En este contexto, el lengua= je actúa como vehículo por la transmisión y perseveraci&o= acute;n de la identidad cultural.

La identidad cultural adquiere releva= ncia en aquellos contextos en que coexisten diferentes lenguas y culturas, como = es el caso de Cataluña. Esta comunidad autónoma es bilingüe, con dos lenguas oficiales: catalán y español. Además, = como consecuencia de los procesos migratorios que han ocurrido en las últ= imas décadas, Cataluña se ha convertido en un territorio multilingüe y multicultural, lo que la caracteriza como una zona de al= ta complejidad cultural y lingüística (IDESCAT, 2024).<= /span>

En consecuencia, el presente estudio pretende explorar la dominancia lingüística como una herramient= a de reafirmación de la identidad cultural, examinando cómo los us= os lingüísticos, las actitudes y las competencias pueden ejercer u= na influencia en la perseveración, reafirmación y transformación de las identidades culturales en el contexto de Cataluña.   <= /o:p>

 

 

2.   MARCO TEÓRICO

 

2.1 El concepto de identidad cultural

 

En los últimos años, el concepto de identidad cultural ha evolucionado de ser una noción estática a un fenómeno complejo y dinámico, un cambio impulsado en gran medida por la interacción de los individuos con prácticas sociales que continuamente modelan y redefinen la identidad (Vallejo y Tonioli, 2023). En este contexto de transformación destaca el trabajo de Kaplan y Garner (2017), el cual introdujo el Modelo de Sistemas Dinámicos de Identidad de Roles (DSMRI). Este enfoque metateórico considera la identidad como un sis= tema complejo y dinámico, compuesto por creencias, intenciones, metas, autopercepciones, autodefiniciones y opciones de acción. El hecho de= que sea un sistema dinámico complejo quiere decir que este sistema no pu= ede reducirse a sus componentes aislados, sino que estos deben considerarse com= o un conjunto interdependiente, tal como lo destacan estudios complementarios (B= ar-Yam, 2019; Butz, 2018; Guastello y Leibovitch, 2= 008). El modelo DSMRI sugiere que la identidad de roles se enmar= ca dentro de una estructura multinivel, donde en el ámbito perso= nal refleja un sistema complejo de diferentes identidades de rol. Esta identida= d, lejos de ser estática, se encuentra en un estado constante de desarr= ollo y transformación, influenciada por interacciones tanto personales co= mo sociales y mediatizada por factores sociocognitivos y culturales.

Sin embargo, el DSMRI trata la identidad cultural como una estructura multinivel, la cual emerge en la medida en la = que las personas se identifican con su cultura, influenciada significativamente= por el papel social que desempeñan (Clark, 1990; Ha= mers, 2004). Además, el modelo enfatiza que la identidad cultural es produ= cto de una continua reconfiguración y reorganización, propiciada = por interacciones tanto interpersonales como intrapersonales, bajo la influenci= a de factores sociocognitivos y culturales (Kaplan y Garner, 2017). Por lo tanto= , la identidad cultural se ve como un elemento dinámico, adaptable y en constante evolución (Puri, 2008). Kaplan y Garner (2017) profundizan= en señalar que el sistema de roles incluye tres aspectos fundamentales: contenido, estructura y proceso de formación, que son dinámic= os y susceptibles a cambios según el tiempo y el contexto, subrayando la flexibilidad y la susceptibilidad a modificaciones de la identidad cultural= .

Estudios de investigadores como Sen (2007= ) y Marcu (2012) ilustran cómo los individuos pued= en desarrollar identidades múltiples o híbridas como resultado d= e la exposición a diferentes culturas, destacando el concepto de "biculturalismo", que describe a personas que se implican activamente en dos o más culturas, fusionando y mezclando aspectos de cada una (Grosjean, 2010). Esta visión amplia de la identidad cultural, que algunos autores ven como parte de un concepto más extenso de identidad individual (Jameson, 2007), mientras que otros la definen específicamente en térmi= nos de identidad cultural (Castells, 1998), resalta la naturaleza compleja y multinivel de la identidad cultural, incluyendo componentes tanto individua= les como colectivos (Matsumoto, 2003), y enfatiza su carácter multifacético y evolutivo.

En este contexto, el sistema de identidad tiene una tendencia a organizarse hacia la coherencia y la integració= ;n mediante elementos simbólicos externos, como sería por ejempl= o la lengua (Kaplan y Garner, 2017). Esta perspectiva destaca la dinámica evolutiva de la identidad cultural, = que es especialmente evidente en contextos biculturales, donde las personas negocian con sus identidades empleando la lengua como una herramienta que contribuye a la coherencia e integración de la identidad.=

 

2.2 Los elementos de dominancia lingüísti= ca: usos, actitudes y competencias

 

A pesar de ser = un aspecto muy presente en el panorama social actual, el bilingüismo es un concepto que no tiene una definición precisa, lo que evidencia una f= alta de consenso en su caracterización desde diferentes perspectivas. Por ejemplo, Bloomfield (1935, citado en Roberts, 20= 13) lo define como el control de dos lenguas de manera similar a un nativo mientras que Mackey (2005) lo describe como la capacidad de producir expresiones completas y significativas en otra lengua.

Un factor relevante en el bilingüismo es la edad de adquisición de= una lengua, ya que este hecho influye en el desarrollo de las habilidades lingüísticas (DeKeyser, 2000; Yeni-Komshian et al., 2000). Se ha visto que el hecho= de adquirir dos lenguas en edades tempranas supone una importante ventaja, por= que ayuda a una mejor adquisición de varios componentes del sistema lingüístico del L2. De esta forma, Amengual (2019, 2024), descr= ibe un tipo de bilingües que son los bilingües tempranos, que son aquellos que han adquirido las dos lenguas en edades tempranas (sea simultánea o sucesivamente).

En contextos bilingües es frecuente que una de las dos lenguas experiment= e un desarrollo más acelerado o pueda mostrar una mayor complejidad, a es= ta lengua se le denomina lengua dominante (Yip y Matthews, 2006). Valdés (2014) considera el bilingüismo como un continuum en el que se represe= nta las dos lenguas habladas y una puede mostrarse más dominante que la otra, o no. Según la competencia adquirida en la segunda lengua se p= uede clasificar para el individuo bilingüe en este continuum desde monolingüe hasta bilingüe equilibrado. = El dominio lingüístico se caracteriza por tres dimensiones claves:= las competencias lingüísticas (que hace referencia a que tan bien se conocen las dos lenguas, sea de manera productiva o perceptiva), el uso de = la lengua (con qué frecuencia los bilingües utilizan sus idiomas y cómo se dividen en ámbitos de su vida), y las actitudes lingüísticas (referente al valor emocional que produce una leng= ua y su uso) (Fishman, 1969; Gertken et al., 2014; Gr= osjean, 2010). Pero la terminología en este ámbito todav&iacut= e;a genera controversia, dificultando un consenso sobre la conceptualizaci&oacu= te;n de la dominancia lingüística (Unsworth, 2015).

L= as actitudes, los usos y las competencias lingüísticas son element= os que se desarrollan de manera interrelacionada. Las actitudes lingüísticas reflejan la predisposición favorable o desfavorable hacia una lengua, su uso y aprendizaje (U= balde et al., 2017). Según Huget y González-Riaño (2004), existen tres elementos principales cap= aces de configurar las actitudes lingüísticas: (a) las necesidades personales, relacionadas con los beneficios o ventajas percibidas de adquir= ir una lengua para su uso instrumental, (b) el grupo social, relacionado con l= as influencias que ejerce el grupo social de referencia y la necesidad de aprobación social del hablante,&nbs= p; y (c) el acceso a cada una de las lenguas, como el grado de presenci= a y accesibilidad de la lengua objetivo al territorio de acogida. Varios autores afirman que las actitudes lingüísticas tienen una influencia en aspectos como decidir qué lengua utilizar en las interacciones diari= as (Bourhis, 1984) y qué lenguas aprender (Gardner, 1982). También, se ha visto que la competencia lingüísti= ca que tiene el individuo sobre una lengua afecta a las actitudes lingüísticas que se desarrollan sobre esta (Lasagabaster, 2003). Por lo tanto, las actitudes lingüísticas de los individuos hacia una lengua están relacionadas tanto con la competencia lingüística como el uso de la lengua, lo que destaca la natural= eza multidimensional del lenguaje.

De forma similar, se ha visto que las actitudes lingüísticas tienen cierta influencia en la identidad territorial que desarrolla la persona (Senar et al., 2023). Divers= os estudios señalan la importancia que ejerce la lengua a la hora de fo= rmar la identidad cultural de una persona (Fielding y <= span style=3D'mso-bookmark:_Hlk179544505'>Harbon, 2013; Pretelt y Katia, 2016; Rodríguez y Tenjo, 201= 9; Schroeder y Marian,2017; Siebenhütter, 202= 3; Trisnawati, 2017) especialmente, en aquellas comunida= des bilingües en las que conviven las lenguas y culturas autónomas (Larrañaga et al.,2016). Este es el caso de Cataluña, donde la lengua y culturas autónomas se han convertido convirtiéndo= se en una herramienta para expresar la identidad (Bourhis= y Giles, 1977; Segalowitz et al., 2009), y vinc= ularse con la identidad cultural a través del aprendizaje y la participación cultural (Schroeder y Marian, 2017).

E= n la pretensión de integrar el análisis del bilingüismo con el DSMRI, se desprende la idea de que la dominancia lingüística pu= ede funcionar como un estado atractor conceptual hacia el sistema de identidad = de rol que desarrolla una persona en una cultura (Kaplan y Garner, 2017), es decir, su identidad cultural empleando la lengua como una herramienta para reafirmar la identidad cultural del individuo.

<= o:p> 

2.3. Idiosincrasia cultural y lingüística del contexto catalá= n

<= o:p> 

El presente estudio se centra en Lleida, una provincia de Cataluña (España) en la que coexisten el catalán y el castellano como lenguas oficiales. Con la aprobaci&oacu= te;n del estatuto de 1979, la Generalitat de Cataluña ha implementado políticas para promover la normalización del catalán c= on la finalidad de fortalecer el catalán como signo de identidad y elem= ento definitorio de Cataluña (Berché, = 2013), ya que la lengua catalana es considerada esencial para Cataluña, desempeñando un papel fundamental en la comunicación, integración y cohesión social de los ciudadanos (Pujolar, 2010).

Con el fin de contextualizar adecuadamente la actual situación identitaria y lingüística del territorio catalán, es importante conocer el desarrollo de las dos identidades predominantes en las últimas décadas. Durante la dictadura franquista, en el siglo XX, se legitimó la identidad nacional española como la única, subestimando y prohibiendo las identidades y lenguas regionales. Con la promulgación de la Constitución española en 1978, se abrió la puerta al resurgimiento de estas identidades regionales. La Constitución declaró el castellano como lengua nacional, pero también permitió el desarrollo de la educación y los servicios gubernamentales autonómicos en las lenguas regionales (Montaruli et al., 2011).

En consecuencia, cada comunidad autó= noma emprendió la aprobación de leyes destinadas a revitalizar sus lenguas y culturas regionales respectivas (Fishman, 1991), reflejando así perfiles lingüísticos y étnicos distintivos q= ue se basan en sus características históricas, económicas, sociales, demográficas y políticas (Leco= urs, 2001; Montaruli et al., 2011). Este proceso dio= lugar a la emergencia de identidades prototípicas diversas, que se entiend= en como continuo, abarcando desde la identidad exclusivamente española, pasando por diversas permutaciones de identidades duales española/autonómica hasta la identidad exclusivamente autonómica (Montaruli et al., 2011; Ros = et al., 1999). Ros et al., (1999) adopta el concepto de identidad comparativa,= que hace referencia a la simultánea identificación con dos nivele= s de inclusión, en el caso de los catalanes, esta identidad comparativa es alta, lo que viene a decir que se identifican más como catalanes que como españoles (Huici y Ros, 1993; Ros et al., 1994; Ros et al., 199= 9)

De tal forma, la lengua catalana está contemplada como un elemento clave en la definición de la identidad catalana, actuando como un factor de inclusión social que abarca tan= to a los catalanes autóctonos como a los inmigrantes (Berché, 2013). Esta comunidad ha experimentado un proceso migratorio significativo = en los últimos años, concretamente, en el año 2022 un 21,= 2% de la población catalana son de origen extranjero y un 15,2% han nac= ido en el resto del país y han inmigrado posteriormente a Cataluña (IDESCAT, 2024). Esta diversidad poblacional otorga a Cataluña un carácter plurilingüe, a pesar de su condición oficial co= mo bilingüe.

Otro rasgo definitorio de esta comunidad es= su carácter multicultural, donde conviven la cultura catalana y española. Además, estas dos culturas están en contacto= con otras debido al proceso migratorio. La identidad catalana a lo largo del ti= empo se ha construido en torno a un conjunto de elementos culturales, uno de los más desacatados es la lengua catalana y según Lapresta-Rey et al. (2020), el catalán y el castellano son dos lenguas oficiales asociadas a identidades territoriales habitualmente conceptualizadas como opuestas. Por lo tanto, una parte importante de la población entiend= e la identidad catalana como antagónicamente relacionada con la española (Berché, 2013; Villa et = al., 2010; Ros et al., 1994; Ros et al., 1999).

El estudio de Montarul= i et al. (2011) profundizó en las posibles identidades lingüísticas y étnicas que existen en las comunidades autónomas bilingües, rastreando el porcentaje de participantes = que adoptaban una identidad prototípica junto con sus principales correl= atos sociopsicológicos. La Figura 1 del estudio muestra varias combinacio= nes posibles entre grados débiles, moderados y fuertes de identidad con = las lenguas y las culturas autonómicas y españolas, ofreciendo una representación visual de esta compleja dinámica identitaria en estas comunidades autónomas.

 

Nota. El número de participant= es que entran dentro de un prototipo de identidad es N=3D 1584 (67,0% de la mu= estra total, N=3D2365). Los seis grupos de identificación retenidos en el análisis

 (Cuadrados sombreados) corresponden= a N=3D1533 (64,8% de la muestra total, N=3D2365). Extraído de Montaruli et al. (2011).

 

Figura 1. <= i>Nueve prototipos de identidad por individuos de origen español y autonómico

 

Según este modelo, el desarrol= lo de la sensibilidad intercultural aparece en dos Existen varios factores que influyen en el grado de identificación de los individuos como sería los respectivos orígenes étnicos autonómi= co y español, la competencia y uso de la lengua autonómica o espa&= ntilde;ola, la red individual de contactos étnicos y la vitalidad etnolingüística (exovitalidad y egovitalidad) (Montaruli = et al., 2011). Ros et al., (1999) añaden la calidad de la identidad social, = la red individual de contacto lingüístico (INLC), deseo de la proximidad social con miembros del endogrupo y exogrupo, actitudes evaluativas, percepciones discriminatorias y percepcion= es del clima de las relaciones intergrupales.

 

 

3. OBJETIVOS DEL ESTUDIO

 

Atendiendo a las característic= as culturales y sociolingüísticas del territorio catalán, e= ste estudio tiene como objetivo conocer la manera en que los diferentes element= os que componen la dominancia lingüística actúan como eleme= ntos de expresión identitaria. De forma más concisa, se pretende d= ar respuesta a las siguientes preguntas de investigación:

PI 1: ¿Está el grado de identificación cultural relacionado con el desarrollo de las actitud= es lingüísticas hacia cada una de las lenguas del territorio catalán?

PI 2: ¿Está el grado de identificación cultural relacionado con el nivel de competencia autopercibida de cada una de las lenguas de las lengu= as territorio catalán?

PI 3: ¿Está el grado de identificación cultural relacionado con los usos lingüís= ticos de las lenguas del territorio catalán?

Dada la literatura aportada en los párrafos anteriores, las hipótesis propuestas se articulan de= la siguiente forma:

H1: Se propone que los grupos que se identifiquen predominantemente con la cultura catalana desarrollen una acti= tud más favorable hacia el catalán, mientras que aquellos que se identifiquen predominantemente con la cultura castellana desarrollen una actitud más favorable hacia el castellano.

H2: Se propone que los grupos que se identifiquen predominantemente con la cultura catalana se percibirán más competentes hacia la lengua catalana que los grupos que se identifiquen predominantemente con la cultura española, percibi&eacu= te;ndose estos más competentes hacia la lengua castellana.<= /p>

H3: Se propone que los grupos que se identifiquen predominantemente con la cultura catalana hagan un mayor uso d= e la lengua catalana, mientras que aquellos que se identifican predominantemente= con la cultura española hagan un mayor uso de la lengua castellana.=

 

 

3.   METODOLOGÍA<= /b>

 

4.1. Participantes<= /b>

 

El presente estudio se basó en= una muestra constituida por 393 participantes (288 mujeres, 103 hombres, 2 no binarios; Medad =3D 28.27, DE=3D 12.50). De ellos, el 83% nacieron en Cataluña, el 7.9% nacieron en otra comunidad autónoma espa&nt= ilde;ola y el 9.2% nacieron en otro país. Todos los participantes se encontra= ban residiendo en la provincia de Lleida en el momento del estudio, habiendo residido allí durante el menos un año.

 

4.2. Instrumentos

 

4.2.1. Identificación cultural=

 

La evaluación de la identificación cultural se llevó a cabo mediante un instrumen= to de elaboración propia, basado en los principios teóricos con = los que se desarrolló la Multigroup Etnic Identity Measure (Brown et al., 2014) y adaptado al contexto catalán. El instrumento consta de dos versiones, una que atiende el grado de identificación cultural hacia la cultura catalana y otra po= r la castellana. Cada versión consta de tres constructos, uno que atiende= la exploración cultural, otro a la resolución y el último= que hace referencia a la afirmación y pertenencia. El instrumento consta= de un total de 18 ítems los cuales evalúan cada constructo a través de una escala Likert que va de 1 a 5 en lo que 1 es totalment= e en desacuerdo y 5 totalmente de acuerdo (Ver anexo 1).

En referencia a la fiabilidad de la versión que refiere a la cultura catalana, se obtuvieron valores de fiabilidad y consistencia adecuados para cada uno de los constructos (exploración cultural: α =3D .90, ω =3D .90, AVE =3D .76, = resolución cultural: α =3D .91, ω =3D .92, AVE =3D .78, afirmación y pertenencia: α =3D .91, ω =3D .92, AVE =3D .78). El conjunto tota= l de la prueba mostró valores de fiabilidad y consistencia interna aceptable= s: α =3D .95, ω =3D .95, AVE =3D .71. Por su parte, por la versi&oac= ute;n que refiere a la cultura española, se consiguieron valores de fiabilidad= y consistencia interna igualmente adecuados para cada uno de los constructos (exploración cultural: α =3D .81, ω =3D .81, AVE =3D .59, resolución cultural=3D: α =3D .89, ω =3D .89, AVE =3D .74, afirmación y pertenencia: α =3D .92, ω =3D .92, AVE =3D .7= 9). El conjunto total de la prueba mostró valores de fiabilidad y consisten= cia interna aceptables: α =3D .94, ω =3D .94, AVE =3D .64<= /span>

 

4.2.2. Actitudes lingüíst= icas

 

La evaluación de las actitudes lingüísticas se realizó mediante un instrumento basado en Baker (1992) adaptado al contexto catalán. El instrumento consta de = dos versiones, una que atiende el nivel de actitud lingüística haci= a la lengua catalana y otra hacia la lengua castellana. El cuestionario consta de una escala Likert de un total de 12 ítems para cada una de las versi= ones (catalana y castellana) con 5 opciones de respuestas en las que 1 es totalm= ente en desacuerdo y 5 totalmente de acuerdo. Cada versión consta de tres constructos de cuatro ítems cada uno: actitud afectiva, actitud cognitiva y actitud conductual (Véase anexo 2).

En referencia a la fiabilidad de la versión que refiere a la lengua catalana, se obtuvieron valores de fiabilidad y consistencia interna adecuados para cada uno de los constructos (actitud afectiva: α =3D .90, ω =3D .89, AVE =3D .69, actitud cog= nitiva: α =3D .89, ω =3D .90, AVE =3D .69 y actitud conductual: α = =3D .91, ω =3D .91, AVE =3D .72). El conjunto total de la prueba mostró = valores de fiabilidad y consistencia interna aceptables: α =3D .96, ω =3D= .96, AVE =3D .65. Por su parte, con respecto a la versión que refiere la = lengua española, se consiguieron valores de fiabilidad y consistencia inter= na igualmente adecuados para cada uno de los constructos (actitud afectiva: &#= 945; =3D .87, ω =3D .87, AVE =3D .62, actitud cognitiva: α =3D .81, &#= 969; =3D .82, AVE =3D .60 y actitud conductual: α =3D .90, ω =3D .87, AVE =3D .= 69). El total de la prueba de la muestra mostró valores de fiabilidad y consistencia interna también aceptables: α =3D .94, ω =3D = .94, AVE =3D .58.

 

4.2.3. Usos lingüísticos<= o:p>

 

La evaluación de los usos lingüísticos se realizó mediante un instrumento de elaboración propia en el que se pregunta por el uso de cada una de l= as lenguas evaluadas en diferentes contextos, donde se incluyen hogar, lugar de trabajo, estudios, amigos, medios de comunicación y redes sociales. = El instrumento consta de 10 ítems de escala Likert de 6 puntos donde 1 = es nunca y 6 es siempre (Ver anexo 3).

 

4.2.4. Competencia lingüística autopercibida

 

La evaluación de la competencia lingüística autopercibida se realizó mediante un instrumento de elaboración propia, en el = que se evaluaron competencias referidas a la comprensión y producci&oacu= te;n tanto oral como escrita. El instrumento consta de 8 ítems de escala Likert de 6 puntos, la cual va desde ninguna habilidad hasta hablante nativ= o y bilingüe (Ver Anexo 4).

 

4.2.5. Variables sociodemográf= icas

 

Los participantes proporcionaron información sobre su edad, género, lugar de nacimiento y tiem= po de residencia en Cataluña a través de un cuestionario ad hoc diseñado por los investigadores.

 

4.3. Procedimiento<= /b>

 

La administración y recolección de datos se hizo por un cuestionario vía Microsfot Forms el cual recogía todos los ítems antes mencionados con el fin de evalu= ar todas las variables que se pretende valorar en el presente estudio. El cuestionario fue distribuido y completado por los diferentes participantes = en una sala habilitada y con la supervisión de personal previamente instruido. La duración del cuestionario estuvo de unos 10-15 minutos. Previamente, se obtuvo el consentimiento informado de los participantes, garantizando el anonimato y la confidencialidad de los datos cumpliendo así las normas éticas establecidas por la Comisión Eur= opea (European Commission, 2013).

 

4.4. Tratamiento estadístico

 

El análisis estadístico= se llevó a cabo utilizando el paquete de software = stats del lenguaje de programación R, a través de la interfaz estadística JASP. Como paso previo al análisis de datos, se identificaron y eliminaron a los participantes, los cuales dieron patrones = de respuesta improbables, a través de la distancia de Mahalanobis (Leys et al., 2018). Esto resultó en la eliminación de 11 participantes de los análisis posteriores.<= o:p>

Para categorizar a los participantes = en función de su identidad cultural, se utilizó el procedimiento= de clusterización por K-mean= s. La cantidad de grupos a obtener se determinó por conveniencia, atendiendo a un criterio de sentido teórico.

Para abordar los propósitos de= la investigación se aplicaron estadísticos de comparación basada en el análisis de covariancia (ANCOVA), usando la edad de los participantes como covariable para eliminar su posible efecto sobre la vari= able dependiente.

 

 

 

M

DE=

Asimetría

Curtosis

Catalán

 

 

 

 

 

 

Identidad cultural Total

3.792

1.015

-0.898

0.234

 

    Exploración cultural

3.657

1.042

-0.669

-0.057

 

    Resolución cu= ltural

3.702

1.123

-0.725

-0.257

 

    Afirmación y pertinencia

4.000

1.103

-1.077

 0.358

 

Actitudes lingüísticas Total

3.922

1.003

-1.013

0.293

 

    Actitud afectiva

4.162

0.945

-1.337

1.299

 

    Actitud cognitiva

4.010

1.068

-1.164

0.611

 

    Actitud conductual

3.593

1.195

-0.540

-0.769

 

Usos lingüísticos

4.392

1.408

-0.717

-0.602

 

Competencia lingüística autopercibida

5.495

0.920

-2.324

5.201

Españo= l

 

 

 

 

 

 

Identidad cul= tural Total

2.936

0.967

0.113

-0.593

 

    Exploración cultural

3.201

0.914

-0.145

-0.192

 

    Resolución cu= ltural

2.891

1.097

0.030

-0.806

 

    Afirmación y pertinencia

2.716

1.186

0.227

-0.887

 

Actitudes lingüísticas Total

2.838

1.006

0.313

-0.662

 

    Actitud afectiva

2.953

1.135

0.043

-0.941

 

    Actitud cognitiva

3.104

0.974

0.054

-0.556

 

    Actitud conductual

2.457

1.202

0.543

-0.742

 

Usos lingüísticos

4.079

1.287

-0.135

-1.078

 

Competencia lingüística autopercibida<= span style=3D'font-size:10.0pt;font-family:"Verdana",sans-serif;mso-fareast-la= nguage: ES'>

5.538

0.828

-2.530

6.888

Nota. M=3D media, DE=3DDesviaci&oacut= e;n estándar

 

Tabla 1. Estadísticos Descriptivos de los constructos que componen el análisis

 

 

5.2. Categorización de los participantes en función de su identidad cultural: K-mean clustering

 

La figura 2 muestra los centros de clúster finales de los grupos obtenidos a través del procedimiento de clusterización K-mean. = El número de grupos resultantes ha sido escogido por conveniencia, teni= endo en cuenta un criterio de coherencia teórica (Mo= ntaruli et al., 2011).

 

Nota. Las puntuaciones hacen referencia a los centros de cluster= ización finales.

 

Figura 2. Categorización de= los participantes en función de su identidad cultural. K-mean clustering

 

 

Los resultados de los procedimientos = de clusterización muestran una agrupación = de los participantes en cuatro grupos diferenciados: un primer grupo formado por 25 participantes que muestran una identidad cultural predominantemente española; un segundo grupo formado por 133 que muestran una identidad cultural predominantemente catalana; un tercer grupo formado 181 que muestr= an una identidad cultural equilibrada alta; y finalmente un grupo formado por = 43 participantes los cuales muestran una identidad cultural equilibrada baja.<= o:p>

 

5.3. Comparación de los difere= ntes componentes de la dominancia lingüística en función de la identidad cultural: Análisis de Covarianza

 

En la Tabla 2 se puede observar los estadísticos descriptivos de los diferentes grupos relativos a cada = una de las variables que componen el estudio, así como las diferencias e= ntre los grupos en función de la identidad cultural, inferida mediante estadísticos ANCOVA.

 

Dominancia lingüística

Predominancia española

Predominancia catalana

Equilibrados altos

Equilibrados bajos

F

p

M

SD

M

SD

M

SD

M

SD

Act cat

2.227

0.949

4.585

0.469

3.926

0.783

2.839

0.995

113.451=

<.001

0.474

Act cast<= /span>

3.587

1.091

2.107

0.674

3.377

0.841

2.395

0.750

76.723<= /o:p>

<.001

0.379

Comp cat

4.530

1.353

5.823

0.379

5.555

0.779

4.785

1.465

31.367<= /o:p>

<.001

0.200

Comp cast<= /span>

5.610

0.842

5.498

0.732

5.704

0.598

4.919

1.439

11.542<= /o:p>

<.001

0.084

Uso cat

2.488

1.218

5.295

0.778

4.211

1.330

3.465

1.372

58.769<= /o:p>

<.001

0.319

Uso cast

4.928

1.278

3.316

1.108

4.597

1.077

3.767

1.319

37.638<= /o:p>

<.001

0.230

Nota. Se asumen como significativos valores de p menores de .05

 

Tabla 2. A= ctitud, competencia y uso lingüístico del castellano y el catalá= n: estadísticos descriptivos y ANCOVA

 

Análisis = post-hoc

 

Los análisis post-hoc con corrección de Tukey mostraron que, en referencia a las actitudes lingüísticas hacia el catalán, existen diferencias significativas entre todos los grupos identitarios analizados. En cuanto a = las actitudes lingüísticas hacia el castellano, todos los grupos han presentado diferencias significativas entre sí, excepto entre los gr= upos de predominancia española y equilibrados altos y, entre los grupos predominancia catalana y equilibrados altos (Tabla 3).

 

 <= /o:p>

 <= /o:p>

Mean Difference

SE

t

Cohen's d

Predominancia española

Predominancia catalana

-2.381

0.160

-14.880

3.258

<.001

Equilibrados altos

-1.713

0.156

-10,969

2.345

<.001

Equilibrados bajos

-0.620

0.184

-3.373

0.849

0.005

Predominancia catalana

Equilibrados altos

0.668

0.084

7.981

0.914

<.001

Equilibrados bajos

1.761

0.129

13.694

2.410

<.001

Equilibrados altos

Equilibrados bajos

1.093

0.124

8.813

1.496

<.001

Predominancia española

Predominancia catalana

1.489

0.174

8.534

1.869

<.001

 <= /o:p>

Equilibrados altos

0.215

0.170

1.263

0.270

0.587

 <= /o:p>

Equilibrados bajos

1.194

0.200

5.957

1.499

<.001

Predominancia catalana

Equilibrados altos

-1.274

0.091

-13.964

1.599

<.001

 <= /o:p>

Equilibrados bajos

-0.295

0.140

-2.103

0.370

0.154

Equilibrados altos

Equilibrados bajos

0.979

0.135

7.239

1.229

<.001

Nota. Se asumen como significativos valores de p menores de .05

 

Tabla 3. Diferencias entre grupos por= el constructo de actitudes lingüísticas. Análisis post-hoc

      =           

 

En referencia a las competencias lingüísticas autopercibidas los análisis post-hoc mostraron que, en refe= rencia a las competencias lingüísticas autopercib= idas hacia el catalán, existen diferencias significativas entre todos los grupos identitarios a excepto entre los grupos de predominancia españ= ;ola y equilibrados bajos. En cuanto al castellano, la significación encontrada en el modelo general se debe principalmente a las diferencias en= tre el grupo de equilibrados bajos y el resto de grupos, siendo esta significativamente menor en todos los casos (Tabla 4).

 

 <= /o:p>

 <= /o:p>

Mean Difference

SE

t=

Cohen's d

Predominancia española

Predominancia catalana

-1.348<= /o:p>

0.180

-7.482<= /o:p>

1.638

<.001

Equilibrados altos

-1.059<= /o:p>

0.176

-6.019<= /o:p>

1.286

<.001

Equilibrados bajos

-0.273<= /o:p>

0.207

-1.318<= /o:p>

0.332

0.552

Predominancia catalana

Equilibrados altos

0.289

0.094

3.072

0.352

0.012

Equilibrados bajos

1.075

0.145

7.425

1.307

<.001

Equilibrados altos

Equilibrados bajos

0.786

0.140

5.625

0.995

<.001

Predominancia española

Predominancia catalana

0.101

0.174

0.581

0.127

0.938

 <= /o:p>

Equilibrados altos

-1.101<= /o:p>

0.170

-0.593<= /o:p>

0.127

0.934

 <= /o:p>

Equilibrados bajos

0.688

0.200

3.435

0.864

0.004

Predominancia catalana

Equilibrados altos

-0.202<= /o:p>

0.091

-2.219<= /o:p>

0.254

0.120

 <= /o:p>

Equilibrados bajos

0.587

0.140

4.188

0.737

<.001

Equilibrados altos

Equilibrados bajos

0.789

0.135

5.838

0.641

0.001

Nota. Se asumen como significativos valores de p menores de .05

 

Tabla 4. Diferencias entre grupos = por el constructo de comprensión lingüística autopercibida. An&aacut= e;lisis post-hoc

 

 = ;            &n= bsp;  

En lo referente a los usos lingüísticos, los análisis post-hoc= mostraron que en referencia a las competencias lingüísticas autopercibidas hacia el catalán, hay diferenci= as significativas entre todos los grupos identitarios. En referencia al castellano, hay diferencias significativas entre todos los grupos, excepto entre predominancia española y equilibrados altos, y predominancia catalana y equilibrados bajos (Tabla 5).

 

 

 

 <= /o:p>

 <= /o:p>

Mean Difference

SE

t=

Cohen's d

Predominancia española

Predominancia catalana

-2.814<= /o:p>

0.255

-11.016=

2.412

<.001

Equilibrados altos

-1.727<= /o:p>

0.249

-6.928<= /o:p>

1.481

<.001

Equilibrados bajos

-0.979<= /o:p>

0.293

-3.337<= /o:p>

0.840

0.005

Predominancia catalana

Equilibrados altos

1.086

0.134

8.135

0.931

<.001

Equilibrados bajos

1.834

0.205

8.936

1.573

<.001

Equilibrados altos

Equilibrados bajos

0.748

0.198

3.777

0.641

0.001

Predominancia española

Predominancia catalana

1.577

0.247

6.381

1.397

<.001

 <= /o:p>

Equilibrados altos

0.310

0.241

1.284

0.275

0.573

 <= /o:p>

Equilibrados bajos

1.149

0.284

4.047

1.018

<.001

Predominancia catalana

Equilibrados altos

-1.267<= /o:p>

0.129

-9.807<= /o:p>

1.123

<.001

 <= /o:p>

Equilibrados bajos

-0.428<= /o:p>

0.199

-2.155<= /o:p>

0.379

0.138

Equilibrados altos

Equilibrados bajos

0.839

0.192

4.381

0.744

<.001

Nota. Se asumen como significativos valores de p menores de .05

 

Tabla 5. Diferencias entre grupos = por el constructo de usos lingüísticos.= Análisis post-hoc

 

6. DISCUSIÓN=

 

Con el objetivo de conocer el modo en= que los diferentes elementos que componen la dominancia lingüística operan como elementos de expresión de la identidad cultural, el pres= ente estudio analizó el efecto de la dominancia lingüística s= obre la identidad cultural de la población del territorio catalán.=

En respuesta a la primera pregunta de investigación, la cual plantea que el grado de identificación cultural está relacionada con el desarrollo de las actitudes lingüísticas, los resultados mostraron un efecto significativo = de las actitudes lingüísticas de ambas lenguas (catalán y castellano) sobre la identidad cultural. Estos hallazgos van en consonancia= con lo hipotetizado y apoyan lo encontrado en estudios como Büyükkantarcıoğlu (2006, 2020) los cuales exponen que en comunidades bilingües existe ci= erta relación entre las actitudes lingüísticas con la identid= ad cultural/social. Por lo tanto, tal y como se desprende del modelo DSMRI, las actitudes lingüísticas se desarrollarían paralelamente c= on la identidad cultural en un marco de causalidad recíproca, donde la identidad cultural ejerce un efecto potenciador de las actitudes lingüísticas hacia la lengua asociada y viceversa. Otros estudi= os, como Senar et al. (2023) sugieren que las actit= udes lingüísticas tienen una cierta influencia con la identidad terr= itorial desarrollada por los individuos.

Si bien es cierto que hay una relación entre la identidad cultural y las actitudes lingüísticas, especialmente con respecto a las actitudes lingüísticas hacia el catalán, concretamente, hay que destacar las diferencias con gran efecto encontradas entre los grupos de predominancia española y predominancia catalana. Por el contrario, l= os resultados en el caso del castellano no parecen tan evidentes las diferenci= as entre los grupos de predominancia española y equilibrados altos y en= tre los grupos predominancia catalana y equilibrados altos. Tal y como reflejan= los resultados, las diferencias más notables se dan entre aquellos grupos con una identidad polarizada hacia la española o hacia la catalana. = Una posible explicación a este hecho es que se acostumbran a dar actitud= es y comportamientos contrapuestos entre aquellos individuos que se identifican plenamente con la cultura española y aquellos que lo hacen con la cultura autónoma (Montaruli et al., 2011= ). En el territorio catalán, el castellano y el catalán son lenguas oficiales y, como señala Lapresta-Rey et= al. (2020), habitualmente están asociadas como identidades opuestas, por tanto, aquellos individuos que se identifican predominantemente con la cult= ura catalana desarrollarán actitudes más favorables hacia el catalán y menos favorables hacia el castellano y pasa lo mismo con aquellos que se identifican predominantemente con la cultura castellana,  que desarrollarán una actit= ud más favorable hacia el castellano y menos hacia el catalán, debido a esta tendencia a percibirlas como contrapuestas. 

En cuanto a la segunda pregunta de investigación, la cual plantea que el grado de identificación cultural está relacionada con el nivel de competencia autopercibida hacia cada una de las lenguas, los resu= ltados mostraron que el nivel de competencia autopercibida del español y el catalán ejerce un efecto significativo sobre= el grado de identificación cultural. En este caso, los resultados no indican diferencias tan significativas entre los diferentes grupos identitarios, con respecto al castellano únicamente se encontr&oacut= e; diferencias significativas entre el grupo de equilibrados bajos y el resto = de los grupos. Una explicación posible de este fenómeno está = en el grado de identificación cultural de los individuos, aquellos que = se identifican con una cultura en particular o ambas, tienden a experimentar un componente emocional que influye en su percepción de competencia lingüística. Este hecho da lugar a una percepción sesgad= a de su competencia lingüística, sintiéndose más competentes en la lengua asociada a la cultura con la que se identifican más. En contraste, los individuos pertenecientes al grupo de equilibrados bajos no experimentan un sesgo emocional en la competencia autopercibida, dado que no se identifican fuertemente= con ninguna cultura en particular. Este hecho ha sido apoyado por estudios como Ezquerra (2018) en el que se sugiere que existe una fuerte correlació= ;n entre la competencia autoevaluada de una lengua y las actitudes desarrollad= as hacia esta. Otra explicación plausible es que los individuos pertene= cientes al grupo de equilibrados bajos tengan menos interés en aprender la lengua asociada a una cultura o a otra por el hecho de que estos no se sien= ten fuertemente arraigados a ninguna de ellas. Este hecho también es evidente en el caso del catalán, en el que existen diferencias significativas entre todos los grupos, a excepción de predominancia española y equilibrados bajos.

Finalmente, en referencia a la tercera pregunta de investigación, los resultados sugieren que hay un efecto significativo entre los usos lingüísticos de las lenguas del territorio catalán sobre el grado de identificación cultural, confirmándose de esta manera la tercera hipótesis planteada. Estos resultados son apoyados por el estudio de Montar= uli et al., (2011) en el que se afirma que el uso de la lengua autonómic= a o española es uno de los diversos factores que influyen en el grado de identificación de los individuos. De forma similar, los estudios de = Siebenhütter (2023) y Schroeder et al. (2017) pr= oponen que el uso, el conocimiento y la experiencia del idioma están relacionados con la identificación cultural. En este caso, sí= se ha encontrado diferencias significativas entre todos los grupos identitario= s, a excepción de predominancia española y equilibrados altos, y predominancia catalana y equilibrados bajos en cuanto al uso del castellano. Una posible explicación a este hecho es que los grupos de predominan= cia española y equilibrados altos deben utilizar el castellano con frecuencia porque para ellos es una herramienta de reafirmar y expresar su identidad española en aquellas situaciones en las que pueden elegir qué lengua hablar (si catalán o castellano). Por el contrario= , el grupo de predominancia catalana y equilibrados bajos deben hacer poco uso d= e la lengua castellana porque ambos grupos hacen más uso del catalá= ;n, la diferencia es que los equilibrados bajos hablan más el catal&aacu= te;n que el castellano porque el catalán es la lengua que más prevalece en Lleida, mientras que el grupo de predominancia catalana lo hace como forma de expresar su identidad.

En síntesis, los resultados obtenidos respecto a la relación entre los diferentes componentes de= la dominancia lingüística (actitud lingüística, competencia autopercibida y usos lingüísticos) sobre la identidad cultural, sugieren que los tres componentes se ven afectados por esta, con especial énfasis entre la actitud lingüística y la identidad cultural que fue donde se encontraron los resultados más significativos,  por lo tanto, se puede sugerir que= la actitud lingüística es el componente de la dominancia lingüística más influenciado por la identidad cultural. Pero, cabe destacar que las actitudes lingüísticas hacia una le= ngua están relacionadas tanto con la competencia lingüística = como el uso de la lengua, en consecuencia, las actitudes, los usos y las competencias lingüísticas son elementos que se desarrollan de manera interrelacionada y actúan conjuntamente sobre la identidad cultural del individuo, empleándolo como una herramienta de reafirmación hacia su identidad cultural (Bourh= is, 1984; Lasagabaster, 2003).

El presente estudio ofrece una contribución significativa sobre la comprensión de la relación existente entre la dominancia lingüística y el desarrollo de la identidad cultural en los contextos multilingües. Per= o, hay que hacer ciertas consideraciones para interpretar correctamente los resultados. Primeramente, el estudio pretende dar una visión general= del modo en que los elementos identitarios y de dominancia lingüíst= ica se relacionan entre sí, pero la magnitud de esta relación podría ser diferente cuando se atiende a grupos sociales con características sociales o demográficas específicas. En consecuencia, futuras investigaciones donde se utilicen muestras estratific= adas podrían complementar la información que resulta de este estud= io. A su vez, el estudio atiende la naturaleza dinámica de la identidad cultural, tal y como propone el Modelo de Sistemas Dinámicos de Identidad de Roles (DSMRI) (Kaplan y Garner, 2017). En consecuencia, la magnitud de las diferencias obtenidas entre grupos podría ser también cambiante.

 

 

7. CONCLUSIONES=

 

Este estudio ofrece un análisis detallado de los posibles efectos que los diversos elementos que componen la dominancia lingüística pueden tener sobre la identidad cultural= de los individuos que viven en un entorno donde coexisten múltiples len= guas y culturas, como es el caso de Cataluña. Las ideas clave que se desprenden de los resultados son tres: La primera idea enfatiza el papel de= la identidad cultural como elemento modulador de los diferentes componentes de= la dominancia lingüística, que a su vez actúan como herramientas para reafirmar y expresar esta identidad en contextos multilingües. En segundo lugar, se destaca que aunque todos los componentes de la dominancia lingüística inciden en la identidad cultural, lo hacen de manera desigual. En este sentido, los resultados subr= ayan que las actitudes lingüísticas son el componente que más influye en la identidad cultural. Finalmente, se observa que, si bien la identidad cultural recibe un impacto positivo de los componentes lingüísticos asociados a una cultura determinada, no se observa= un efecto negativo hacia la otra cultura. Por lo tanto, si bien los elementos = de dominancia lingüística actúan como forma de reafirmación cultural, no parece estar asociado a un desprecio o rec= hazo hacia otras identidades culturales.

Estos resultados resaltan la importan= cia de conocer la forma en que la aplicación de diferentes políti= cas lingüísticas influye no sólo en el desarrollo lingüístico, sino que también inciden indirectamente en = la manera en la que las personas perciben y construyen su identidad cultural de aquellos habitantes que residen en territorios de alta complejidad lingüística y cultural, como es el caso de Cataluña.

 

 <= /p>

 <= /p>

REFERENCIAS BIBLIOGRÁFICAS

 

Amengual, M. (2019). Type of early bilingualism and its effect on the acoustic realization of allophonic variants: Early sequen= tial and simultaneous bilinguals. International Journal of Bilingualism<= /i>, 23(5), 954-970.

Amengual, M. (2024). Phonetics of Early Bilingualism. Annual Review of Linguistics, 10, 191-210.=

Baker, C. (1992). Attitudes and language. Multilingual Matters.

Bar-Yam, Y. (2019). Dynamics of complex systems= . CRC Press.

Berché, M. P. (2013). Política lingüística: lengua, cultura e identidad, el ejemplo de Cataluña. Amnis. Revue d'études des sociétés et cultures contemporaines Europe/Amérique. http://amnis.revues.org/2061

Bourhis, R. Y., y Gile= s, H. (1977). The language of intergroup distinctiveness. <= i>Language, ethnicity and intergroup relations, 13, 119.

Bourhis R. Y. (1984). Cross-cultural communication in Montreal: Two field studies since Bill 101. International Journal of the Sociology of Langua= ge, 46, 33–47.

Brown, S. D., Unger Hu, K. A., Mevi, A. A., Hedderson, M. M., Shan, J., Quesenberry, C. P., y Fer= rara, A. (2014). The Multigroup Ethnic Identity Measure—Revised: Measurement invariance across racial and ethnic groups. Journal of counseling psychology, 61(1), 154.

Butz, M. R. (2018). Chaos and complexity: Implications for psychological theory and practice. CRC Press.

Büyükkantarcıo= ğlu, N. (2006). Toplumsal gerçeklik ve dil. Multilingual.

Byers, E., y Yavas, M. (2017). Vowel reduction in word-final position by early and late Spanish-English bilinguals. PloS= one, 12(4), e0175226.

Cast= ells, M. (1998). La era de la información. Economía, sociedad y cultura. vol. II. El poder de la identidad. Alianza.

Clark, T. (1990). International marketing and nati= onal character: A review and proposal for an integrative theory. Journal= of Marketing, 54(4), 66-79.

DeKeyser, R. M. (2000). The robustness of critical period effects in second language acquisition. Studies in second language acquisition, 22(4), 499-533.

European Commission. (2013). Ethics for Researc= hers. In BioScience (Vol. 56).

Ezquerra, A. M. (2018). Analysis of the correlation between self-perceived linguistic competence and language attitudes in the Valencian multilingual context. Foro de Investigación, (23), 545-562.

Fielding, R., y Harbon= , L. (2013). Examining bilingual and bicultural identity in young students. = ;Foreign language annals, 46(4), 527-544.

Fishman, J. A., y Cooper, R. L. (1969). Alternative measures of bilingualism. Journal of Verbal Learning and Verbal Behavior, 8(2), 276-282.

Fishman, J. A. (1991). Reversing language shift: Theoretical and empirical foundations of assistance to threatened languages= (Vol. 76). Multilingual matters.

Gardner, R. C. (1982). Language attitudes and lang= uage learning. Attitudes towards language variation, 132-147.

Generalitat de Catalunya (2024). Informe de polí= tica lingüística 2022. Departament de Cultura. Generalitat de Catalunya.

Generalitat de Catalunya (n.d). Departament de Cultura i <= span class=3DSpellE>llengua. https://cultura.gencat.cat/ca/teme= s/llengua/

Gertken, L. M., Amengu= al, M., y Birdsong, D. (2014). Assessing language dominance with the bilingual language profile.&nb= sp;Measuring L2 proficiency: Perspectivas from SLA, 2= 08, 225.

Grosjean, F. (2010). Bilingualism, biculturalism, = and deafness. International Journal of Bilingual Education and Bilingua= lism, 13(2), 133-145.

Grosjean, F. (2010). Bilingual: Life and realit= y. Harvard University Press.

Grosjean, F. (2015). Bicultural bilingualesInternational Journal of Bilingualism, 19(5), 572-586.

Guastello, S. J., Koopmans, M., y Pincus, D. (Eds.= ). (2008). Chaos and complexity in psychology: The theory of nonlinear dynamical systems. Cambridge University Press.

Hamers, J. F. (2004). A socio= cognitive model of bilingual development. Journal of Language and Social Psychology, 23(1), 70-98.

Huguet, Á., y González-Riaño,= X. A. (2004). Actitudes lingüísticas, lengua familiar y enseñanza de la lengua minoritaria (Vol. 16). HORSORI EDITORIAL, SL.

Huic= i, C., y Ros, M. (1993). Identidad comparativa y diferenciación intergrupal. Psicothema, 225-236.

IDES= CAT. Institut d'Estadística de Catalunya. Usos lingüístics de l= a població. Llengua = inicial, d'identificació i habitual. Disponib= le en línea: https://www.idescat.cat/indicadors/?id=3Danuals&n=3D10364&tema=3Dcu= ltu (consultat el 25 de febrer= del 2024).

Jameson, D. A. (2007). Reconceptualizing cultural identity and its role in intercultural business communication. The Journal of Business Communication (1973), 44(3), 199-235.

Larrañaga, N., Garcia, I., Azurmendi, M. J., y Bourhis, R. (2016). Identity and acculturation: interethnic relations in the Basque Autonomous Community.&nb= sp;Journal of Multilingual and Multicultural Development, 37(2), 131- 149.<= o:p>

Lapresta-Rey, C., Huguet, Á., Petreñas, C., e Ianos, A. (2020). Self-identifications of youth in Catalonia: a linguistic acculturation theory approach. Journal of Multilingual a= nd Multicultural Development, 41(10), 829-843.

Lasagabaster, D. (2003). Attitudes Towards English in the Basque Autonomous Community. World Englishes, 22(4), 585-597.

Lecours, A. (2001). Regionalism, cultural diversity and the state in Spain. Journal of Multilingual and Multicultural Development, 22(3), 210-226.

Leyes, C., Klein, O., Dominic= y, Y., y Ley, C. (2018). Detecting multivariate outliers: Use a robust variant= of the Mahalanobis distance. Journal of experimental social psychology, 74, 150-156.

Kaplan, A., y Garner, J. K. (2017). A complex dyna= mic systems perspective on identity and its development: The dynamic systems mo= del of role identity. Developmental psychology, 53(11), 2036= .

Mackey, W. F. (2005). The description of bilingual= ism. In Language, Communication and Education (pp. 291-307). Routledge.

Marcu, S. (2012). Emotions on the move: belonging, sense of place and feelings identities among young Romanian immigrants in Spain. Journal of Youth Studies, 15(2), 207-223.

Matsumoto, D. (2003). The discrepancy between consensual-level culture and individual-level culture. Culture & Psychology, 9(1), 89-95= .

Montaruli, E., Bourhis= , R. Y., y Azurmendi, M. J. (2011). Identity, language, and ethnic relations in the Bilingual Autonomous Communities of Spain 1. Journal of Sociolinguistics, 15(= 1), 94-121.

Orbea, J. M. M. (2004). Ángel Huguet Canal&ia= cute;s y Xosé A. González Riaño (2004). Actitudes lingüísticas, lengua familiar y enseñanza de la lengua minoritaria. Barcelona: Horsori Editorial. 95 pp., ISBN 84-96108-07-4. = ;Sociolinguistic Studie= s, 410-412.

Pret= elt, M., y Katia, E. (2016). Cultural identity in bilingual schools. <= i>Zona Próxima, (24), 13-27.

Pujolar, J. (2010). Immigration and language education in Catalonia: Between national and social agendas. Linguistics and Education, 21(3), 229-24= 3.

Puri, J. (2008). Encountering nationalism. = John Wiley y Sons.

Roberts, S. G. (2013). Evolutionary approach to bilingualism. [Tesi doctoral, University of Edinburgh]. http://www.cc.gatech.edu/~asb/thesis/ http://hdl.hand= le.net/1842/7995

Rodr= íguez-Tamayo, I. Y., y Tenjo-Macias, L. M. (2019). Children's Cultural Identity Formation: Experiences in a Dual Language Program. <= i>Gist Education and Learning Research Journal, 18, 86-108.<= /span>

Ros, M., Azurmendi, M.= J., Bourhis, R. Y., y García, I. (1999). Identidades culturales y lingüísticas en las Comunidades Autónomas Bilingües (CAB) de España: antecedentes y consecuencias. <= i>Revista de Psicología Social, 14(1), 69-86.

Ros,= M., Huici, C., y Cano, J. I. (1994). Ethnolinguistic vitality and social identity: their impact on ingroup bias and social attribution. International Journal of the sociology of Language= , 1994(108), 145-166.

Schroeder, S. R., Lam, T. Q., y Marian, V. (2017).= Linguistic predictors of cultural identification in bilinguals. Applied linguistics, 38(4), 463-488.

Segalowitz, N., Gatbonton, E., Trofimovich, P., Dörnyei, Z., y Ushioda, E. (2009). Links between ethnolinguistic affiliation, self-related motivation and second language fluency: Are they mediated by psycholinguistic variables. Motivation, language identi= ty and the L2 self, 5(06), 172-192.

Sen, A. (2007). Identity and violence: The illu= sion of destiny. Penguin Books India.

Senar, F., Janés, J., Huguet, Á., y Ubalde, J. (2023). The mosaic of language and identity: territorial identification, linguistic attitudes, and proficiency in young immigrants of Catalonia. International Journal of Multilingualism, 1-17.

Siebenhütter, S. (2023). The multilingual profile and its impact on identity: Approaching the difference between multilingualism and multilingual identit= y or linguistic identity. Ampersand, 10, 100123.

Stölten, K., Abrahamsson, N., y Hyltenstam, K. (2015). Effects of age and speaking rate on voice onset time: The productio= n of voiceless stops by near-native L2 speakers. Studies in Second Langu= age Acquisition, 37(1), 71-100.

Trisnawati, I. K. (2017). Maintaining the identity of bilingual individuals in multicultural/multilingual settings. Englisia<= /i>: Journal of Language, Education, and Humanities, 5(1), 8-16.=

Ubalde, J., Alarcón, A., y Lapresta, C. (2017). Evolution and determinants of language attitudes among Catalan <= span class=3DSpellE>adolescentesInternational Journal of Intercultural Relations, 60, 92-103.

Unsworth, S. (2015). Amount of exposure as a proxy= for dominance in bilingual language acquisition. In C. Silva-Corvalán y = J. Treffers-Daller (Eds.), Language Dominance in Bilinguals: Issues of Measurement and Operationalization (pp. 156–173). Cambridge University Press.

Valdés, G. (2014). Expanding definitions= of giftedness: The case of young interpreters from immigrant communities. Routledge.

Vallejo Rubinstein, C., y Tonioli, V. (2023). Expl= oring the Linguistic and Cultural Identities of Transnational Background Children= in Catalonia, Spain. Societies, 13= (10), 221.

Vila= , I., Esteban Guitart, M., y Oller, J. (2010). Identidad nacional, lengua y escue= la=3D National identity, language and school. = ;Revista de Educación, 353, 39-65.

Yeni-Komshian, G. H., = Flege, J. E., y Liu, S. (2000). Pronunciation proficiency in the first and second languages of Korean–English bilinguals. Bilingualism: Language and cognition, 3(2), 131-149.

Yıldırım, F. Ç. (2020). Lang= uage choice and identity: An investigation based on the comparison of language attitudes from two different localities. Journal of Language and Linguistic Studies, 16(2), 1032-1042.

Yip, V., y Matthews, S. (2006). Assessing language dominance in bilingual acquisition: A case for mean length utterance differentials. Language Assessment Quarterly: An Inter= national Journal, 3(2), 97-116.

 <= /p>

<= o:p> 

 

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