4,541 research outputs found
Dependencia afectiva, violencia y celos en la pareja
No full text[spa] El objetivo de este trabajo fue realizar una revisión teórica sobre la dependencia afectiva, la violencia y los celos de pareja desde un enfoque psicológico. En la primera parte se desarrolló el apego y la dependencia afectiva en las relaciones de pareja, modelos y tipos de apego, enfoque psicológico de los celos (tipos y modelos), definición de violencia, tipos de violencia y violencia contra la pareja. Para la segunda parte, se realizó un análisis no sistemático consultando las bases de datos de Google Académico, Dialnet, Redalcy, PsyInfo, ELSEVIER, Researchgate y Scielo revisando aproximadamente 30 documentos en español e inglés, desde el año 2000 al 2018. De los cuales se describen cuatro investigaciones sobre los principales factores de riesgo sobre la violencia en las relaciones de pareja, la violencia entre parejas adolescentes, violencia entre parejas del mismo género y la ciber agresión; lo que permitió llegar a las conclusiones finales.[eng] The objective of this work was to perform a theoretical review on affective dependence, violence and couple's jealousy from a psychological perspective. In the first part, attachment and affective dependence in couple relationships, models and types of attachment, psychological focus of jealousy (types and models), definition of violence, types of violence and violence against the couple were developed. For the second part, a non-systematic analysis was carried out by consulting the Google Academic, Dialnet, Redalcy, PsyInfo, ELSEVIER, Researchgate and Scielo databases, reviewing approximately 30 documents in Spanish and English, from 2000 to 2018. Of which four investigations are described on the main risk factors on violence in couple relationships, violence between adolescent couples, violence between same-sex couples and cyber-aggression; what allowed to reach the final conclusions
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Alfredo Pareja y Díez Canseco Manuscripts
No full textAlfredo Pareja y Díez Canseco (1908-1993) was born in Guayaquil, Ecuador. Part of the Generación del 30 and the Grupo de Guayaquil as an author, Pareja was also a university professor, Superintendent of Secondary Education, member of Ecuador's National Assembly, head of mission in the United Nations Relief and Rehabilitation Administration, ambassador of Ecuador in France and to UNESCO, and Ecuador's Minister of Foreign Relations from 1979 to 1980. He wrote a number of novels and historical texts, including El Muelle (1933), Hombres sin tiempo (1941), La Manticora (1974) and Historia del Ecuador (1954). Among numerous honors, Pareja was awarded the Medalla Premio Nacional de Cultura Eugenio Espejo and the Gran Cruz de la Orden al Mérito del Ecuador, and Spain's Gran Cruz de Isabel la Católica. His manuscript collection includes digitized manuscripts of "El Muelle" (1932), "Las Pequeñas estaturas" (1966), and "Los Poderes omnimodos" (c.1964).Digitized manuscripts of works by Ecuadorian author and historian Alfredo Pareja y Díez Canseco include "El Muelle" (1932), "Las Pequeñas estaturas" (1966), and "Los Poderes omnimodos" (c.1964).UT Librarie
Una visión familiar de Alfredo Pareja Diezcanseco (Testimonios)
No full textEl escritor Miguel Donoso Pareja confiesa que en su vida existieron dos modelos: el de su padre -hasta reconocer que no era capaz de emular al navegante y matemático-, y el de su tío Alfredo Pareja. Admira al escritor tanto como al ser humano: por su deseo permanente de aprender y la exigencia implacable consigo mismo, cuanto por su vitalidad. Recuerda las visitas familiares, cada semana, de su tío a la Península de Santa Elena, aprobaba en silencio las lecturas juveniles de Donoso, e impuso un quiebre de calidad con Las mil noches y una noche. Como estudiante en casa de su abuela materna en Guayaquil, el autor conoció a otro Alfredo Pareja: el de su agitada rutina diaria de escritor y hombre de negocios, visitaba su casa, fascinado por su inmensa biblioteca, a la que tenía libre acceso, poco después, su tío Alfredo iniciaría sus largos años de viajero, y se reencontrarían pocas veces, en Quito, en la década de 1980. El autor concluye la emotiva reseña con una breve síntesis valorativa de la producción de Pareja Diezcanseco.The writer Miguel Donoso Pareja confesses that two models existed in his life: that of his father- even as he recognized that he was not capable of emulating the sailor and the mathematician-, and that of his uncle Alfredo Pareja. He admires the writer as well as the human being: for his permanent desire to learn and the implacable demands he made on himself, more so his vitality. He remembers the family visits, each week, of his uncle to the Península of Santa Elena, he approved, in silence, the juvenile lectures of Donoso, and imposed certain standards in Las mil noches y una noche. The author got to know a different Alfredo Pareja when as a student he used to visit his maternal grandmother's house in Guayaquil: the busy daily routine 01 a writer and businessman, he used to visit his house, fascinated by his immense library to which he had free access. A little later his uncle Alfredo would begin his long years as a traveler and they would reencounter each other a few times in Quito during the 1980's. The author concludes the emotional review with a short synthesis and assessment of Pareja Diezcanseco's output
OntoTag - A Linguistic and Ontological Annotation Model Suitable for the Semantic Web
No full textOntoTag - A Linguistic and Ontological Annotation Model Suitable for the Semantic Web
1. INTRODUCTION. LINGUISTIC TOOLS AND ANNOTATIONS: THEIR LIGHTS AND SHADOWS
Computational Linguistics is already a consolidated research area. It builds upon the results of other two major ones, namely Linguistics and Computer Science and Engineering, and it aims at developing computational models of human language (or natural language, as it is termed in this area). Possibly, its most well-known applications are the different tools developed so far for processing human language, such as machine translation systems and speech recognizers or dictation programs.
These tools for processing human language are commonly referred to as linguistic tools. Apart from the examples mentioned above, there are also other types of linguistic tools that perhaps are not so well-known, but on which most of the other applications of Computational Linguistics are built. These other types of linguistic tools comprise POS taggers, natural language parsers and semantic taggers, amongst others. All of them can be termed linguistic annotation tools.
Linguistic annotation tools are important assets. In fact, POS and semantic taggers (and, to a lesser extent, also natural language parsers) have become critical resources for the computer applications that process natural language. Hence, any computer application that has to analyse a text automatically and ‘intelligently’ will include at least a module for POS tagging. The more an application needs to ‘understand’ the meaning of the text it processes, the more linguistic tools and/or modules it will incorporate and integrate.
However, linguistic annotation tools have still some limitations, which can be summarised as follows:
1. Normally, they perform annotations only at a certain linguistic level (that is, Morphology, Syntax, Semantics, etc.).
2. They usually introduce a certain rate of errors and ambiguities when tagging. This error rate ranges from 10 percent up to 50 percent of the units annotated for unrestricted, general texts.
3. Their annotations are most frequently formulated in terms of an annotation schema designed and implemented ad hoc.
A priori, it seems that the interoperation and the integration of several linguistic tools into an appropriate software architecture could most likely solve the limitations stated in (1). Besides, integrating several linguistic annotation tools and making them interoperate could also minimise the limitation stated in (2). Nevertheless, in the latter case, all these tools should produce annotations for a common level, which would have to be combined in order to correct their corresponding errors and inaccuracies. Yet, the limitation stated in (3) prevents both types of integration and interoperation from being easily achieved.
In addition, most high-level annotation tools rely on other lower-level annotation tools and their outputs to generate their own ones. For example, sense-tagging tools (operating at the semantic level) often use POS taggers (operating at a lower level, i.e., the morphosyntactic) to identify the grammatical category of the word or lexical unit they are annotating. Accordingly, if a faulty or inaccurate low-level annotation tool is to be used by other higher-level one in its process, the errors and inaccuracies of the former should be minimised in advance. Otherwise, these errors and inaccuracies would be transferred to (and even magnified in) the annotations of the high-level annotation tool.
Therefore, it would be quite useful to find a way to
(i) correct or, at least, reduce the errors and the inaccuracies of lower-level linguistic tools;
(ii) unify the annotation schemas of different linguistic annotation tools or, more generally speaking, make these tools (as well as their annotations) interoperate.
Clearly, solving (i) and (ii) should ease the automatic annotation of web pages by means of linguistic tools, and their transformation into Semantic Web pages (Berners-Lee, Hendler and Lassila, 2001). Yet, as stated above, (ii) is a type of interoperability problem. There again, ontologies (Gruber, 1993; Borst, 1997) have been successfully applied thus far to solve several interoperability problems. Hence, ontologies should help solve also the problems and limitations of linguistic annotation tools aforementioned.
Thus, to summarise, the main aim of the present work was to combine somehow these separated approaches, mechanisms and tools for annotation from Linguistics and Ontological Engineering (and the Semantic Web) in a sort of hybrid (linguistic and ontological) annotation model, suitable for both areas. This hybrid (semantic) annotation model should (a) benefit from the advances, models, techniques, mechanisms and tools of these two areas; (b) minimise (and even solve, when possible) some of the problems found in each of them; and (c) be suitable for the Semantic Web. The concrete goals that helped attain this aim are presented in the following section.
2. GOALS OF THE PRESENT WORK
As mentioned above, the main goal of this work was to specify a hybrid (that is, linguistically-motivated and ontology-based) model of annotation suitable for the Semantic Web (i.e. it had to produce a semantic annotation of web page contents). This entailed that the tags included in the annotations of the model had to (1) represent linguistic concepts (or linguistic categories, as they are termed in ISO/DCR (2008)), in order for this model to be linguistically-motivated; (2) be ontological terms (i.e., use an ontological vocabulary), in order for the model to be ontology-based; and (3) be structured (linked) as a collection of ontology-based triples, as in the usual Semantic Web languages (namely RDF(S) and OWL), in order for the model to be considered suitable for the Semantic Web.
Besides, to be useful for the Semantic Web, this model should provide a way to automate the annotation of web pages. As for the present work, this requirement involved reusing the linguistic annotation tools purchased by the OEG research group (http://www.oeg-upm.net), but solving beforehand (or, at least, minimising) some of their limitations. Therefore, this model had to minimise these limitations by means of the integration of several linguistic annotation tools into a common architecture. Since this integration required the interoperation of tools and their annotations, ontologies were proposed as the main technological component to make them effectively interoperate. From the very beginning, it seemed that the formalisation of the elements and the knowledge underlying linguistic annotations within an appropriate set of ontologies would be a great step forward towards the formulation of such a model (henceforth referred to as OntoTag).
Obviously, first, to combine the results of the linguistic annotation tools that operated at the same level, their annotation schemas had to be unified (or, preferably, standardised) in advance. This entailed the unification (id. standardisation) of their tags (both their representation and their meaning), and their format or syntax. Second, to merge the results of the linguistic annotation tools operating at different levels, their respective annotation schemas had to be (a) made interoperable and (b) integrated. And third, in order for the resulting annotations to suit the Semantic Web, they had to be specified by means of an ontology-based vocabulary, and structured by means of ontology-based triples, as hinted above. Therefore, a new annotation scheme had to be devised, based both on ontologies and on this type of triples, which allowed for the combination and the integration of the annotations of any set of linguistic annotation tools. This annotation scheme was considered a fundamental part of the model proposed here, and its development was, accordingly, another major objective of the present work.
All these goals, aims and objectives could be re-stated more clearly as follows:
Goal 1: Development of a set of ontologies for the formalisation of the linguistic knowledge relating linguistic annotation.
Sub-goal 1.1: Ontological formalisation of the EAGLES (1996a; 1996b) de facto standards for morphosyntactic and syntactic annotation, in a way that helps respect the triple structure recommended for annotations in these works (which is isomorphic to the triple structures used in the context of the Semantic Web).
Sub-goal 1.2: Incorporation into this preliminary ontological formalisation of other existing standards and standard proposals relating the levels mentioned above, such as those currently under development within ISO/TC 37 (the ISO Technical Committee dealing with Terminology, which deals also with linguistic resources and annotations).
Sub-goal 1.3: Generalisation and extension of the recommendations in EAGLES (1996a; 1996b) and ISO/TC 37 to the semantic level, for which no ISO/TC 37 standards have been developed yet.
Sub-goal 1.4: Ontological formalisation of the generalisations and/or extensions obtained in the previous sub-goal as generalisations and/or extensions of the corresponding ontology (or ontologies).
Sub-goal 1.5: Ontological formalisation of the knowledge required to link, combine and unite the knowledge represented in the previously developed ontology (or ontologies).
Goal 2: Development of OntoTag’s annotation scheme, a standard-based abstract scheme for the hybrid (linguistically-motivated and ontological-based) annotation of texts.
Sub-goal 2.1: Development of the standard-based morphosyntactic annotation level of OntoTag’s scheme. This level should include, and possibly extend, the recommendations of EAGLES (1996a) and also the recommendations included in the ISO/MAF (2008) standard draft.
Sub-goal 2.2: Development of the standard-based syntactic annotation level of the hybrid abstract scheme. This level should include, and possibly extend, the recommendations of EAGLES (1996b) and the ISO/SynAF (2010) standard draft.
Sub-goal 2.3: Development of the standard-based semantic annotation level of OntoTag’s (abstract) scheme.
Sub-goal 2.4: Development of the mechanisms for a convenient integration of the three annotation levels already mentioned. These mechanisms should take into account the recommendations included in the ISO/LAF (2009) standard draft.
Goal 3: Design of OntoTag’s (abstract) annotation architecture, an abstract architecture for the hybrid (semantic) annotation of texts (i) that facilitates the integration and interoperation of different linguistic annotation tools, and (ii) whose results comply with OntoTag’s annotation scheme.
Sub-goal 3.1: Specification of the decanting processes that allow for the classification and separation, according to their corresponding levels, of the results of the linguistic tools annotating at several different levels.
Sub-goal 3.2: Specification of the standardisation processes that allow (a) complying with the standardisation requirements of OntoTag’s annotation scheme, as well as (b) combining the results of those linguistic tools that share some level of annotation.
Sub-goal 3.3: Specification of the merging processes that allow for the combination of the output annotations and the interoperation of those linguistic tools that share some level of annotation.
Sub-goal 3.4: Specification of the merge processes that allow for the integration of the results and the interoperation of those tools performing their annotations at different levels.
Goal 4: Generation of OntoTagger’s schema, a concrete instance of OntoTag’s abstract scheme for a concrete set of linguistic annotations. These linguistic annotations result from the tools and the resources available in the research group, namely
• Bitext’s DataLexica (http://www.bitext.com/EN/datalexica.asp),
• LACELL’s (POS) tagger (http://www.um.es/grupos/grupo-lacell/quees.php),
• Connexor’s FDG (http://www.connexor.eu/technology/machinese/glossary/fdg/), and
• EuroWordNet (Vossen et al., 1998).
This schema should help evaluate OntoTag’s underlying hypotheses, stated below. Consequently, it should implement, at least, those levels of the abstract scheme dealing with the annotations of the set of tools considered in this implementation. This includes the morphosyntactic, the syntactic and the semantic levels.
Goal 5: Implementation of OntoTagger’s configuration, a concrete instance of OntoTag’s abstract architecture for this set of linguistic tools and annotations. This configuration (1) had to use the schema generated in the previous goal; and (2) should help support or refute the hypotheses of this work as well (see the next section).
Sub-goal 5.1: Implementation of the decanting processes that facilitate the classification and separation of the results of those linguistic resources that provide annotations at several different levels (on the one hand, LACELL’s tagger operates at the morphosyntactic level and, minimally, also at the semantic level; on the other hand, FDG operates at the morphosyntactic and the syntactic levels and, minimally, at the semantic level as well).
Sub-goal 5.2: Implementation of the standardisation processes that allow (i) specifying the results of those linguistic tools that share some level of annotation according to the requirements of OntoTagger’s schema, as well as (ii) combining these shared level results. In particular, all the tools selected perform morphosyntactic annotations and they had to be conveniently combined by means of these processes.
Sub-goal 5.3: Implementation of the merging processes that allow for the combination (and possibly the improvement) of the annotations and the interoperation of the tools that share some level of annotation (in particular, those relating the morphosyntactic level, as in the previous sub-goal).
Sub-goal 5.4: Implementation of the merging processes that allow for the integration of the different standardised and combined annotations aforementioned, relating all the levels considered.
Sub-goal 5.5: Improvement of the semantic level of this configuration by adding a named entity recognition, (sub-)classification and annotation subsystem, which also uses the named entities annotated to populate a domain ontology, in order to provide a concrete application of the present work in the two areas involved (the Semantic Web and Corpus Linguistics).
3. MAIN RESULTS: ASSESSMENT OF ONTOTAG’S UNDERLYING HYPOTHESES
The model developed in the present thesis tries to shed some light on (i) whether linguistic annotation tools can effectively interoperate; (ii) whether their results can be combined and integrated; and, if they can, (iii) how they can, respectively, interoperate and be combined and integrated. Accordingly, several hypotheses had to be supported (or rejected) by the development of the OntoTag model and OntoTagger (its implementation).
The hypotheses underlying OntoTag are surveyed below. Only one of the hypotheses (H.6) was rejected; the other five could be confirmed.
H.1 The annotations of different levels (or layers) can be integrated into a sort of overall, comprehensive, multilayer and multilevel annotation, so that their elements can complement and refer to each other.
• CONFIRMED by the development of:
o OntoTag’s annotation scheme,
o OntoTag’s annotation architecture,
o OntoTagger’s (XML, RDF, OWL) annotation schemas,
o OntoTagger’s configuration.
H.2 Tool-dependent annotations can be mapped onto a sort of tool-independent annotations and, thus, can be standardised.
• CONFIRMED by means of the standardisation phase incorporated into OntoTag and OntoTagger for the annotations yielded by the tools.
H.3 Standardisation should ease:
H.3.1: The interoperation of linguistic tools.
H.3.2: The comparison, combination (at the same level and layer) and integration (at different levels or layers) of annotations.
• H.3 was CONFIRMED by means of the development of OntoTagger’s ontology-based configuration:
o Interoperation, comparison, combination and integration of the annotations of three different linguistic tools (Connexor’s FDG, Bitext’s DataLexica and LACELL’s tagger);
o Integration of EuroWordNet-based, domain-ontology-based and named entity annotations at the semantic level.
o Integration of morphosyntactic, syntactic and semantic annotations.
H.4 Ontologies and Semantic Web technologies (can) play a crucial role in the standardisation of linguistic annotations, by providing consensual vocabularies and standardised formats for annotation (e.g., RDF triples).
• CONFIRMED by means of the development of OntoTagger’s RDF-triple-based annotation schemas.
H.5 The rate of errors introduced by a linguistic tool at a given level, when annotating, can be reduced automatically by contrasting and combining its results with the ones coming from other tools, operating at the same level. However, these other tools might be built following a different technological (stochastic vs. rule-based, for example) or theoretical (dependency vs. HPS-grammar-based, for instance) approach.
• CONFIRMED by the results yielded by the evaluation of OntoTagger.
H.6 Each linguistic level can be managed and annotated independently.
• REJECTED: OntoTagger’s experiments and the dependencies observed among the morphosyntactic annotations, and between them and the syntactic annotations.
In fact, Hypothesis H.6 was already rejected when OntoTag’s ontologies were developed. We observed then that several linguistic units stand on an interface between levels, belonging thereby to both of them (such as morphosyntactic units, which belong to both the morphological level and the syntactic level). Therefore, the annotations of these levels overlap and cannot be handled independently when merged into a unique multileveled annotation.
4. OTHER MAIN RESULTS AND CONTRIBUTIONS
First, interoperability is a hot topic for both the linguistic annotation community and the whole Computer Science field. The specification (and implementation) of OntoTag’s architecture for the combination and integration of linguistic (annotation) tools and annotations by means of ontologies shows a way to make these different linguistic annotation tools and annotations interoperate in practice.
Second, as mentioned above, the elements involved in linguistic annotation were formalised in a set (or network) of ontologies (OntoTag’s linguistic ontologies).
• On the one hand, OntoTag’s network of ontologies consists of
− The Linguistic Unit Ontology (LUO), which includes a mostly hierarchical formalisation of the different types of linguistic elements (i.e., units) identifiable in a written text;
− The Linguistic Attribute Ontology (LAO), which includes also a mostly hierarchical formalisation of the different types of features that characterise the linguistic units included in the LUO;
− The Linguistic Value Ontology (LVO), which includes the corresponding formalisation of the different values that the attributes in the LAO can take;
− The OIO (OntoTag’s Integration Ontology), which
Includes the knowledge required to link, combine and unite the knowledge represented in the LUO, the LAO and the LVO;
Can be viewed as a knowledge representation ontology that describes the most elementary vocabulary used in the area of annotation.
• On the other hand, OntoTag’s ontologies incorporate the knowledge included in the different standards and recommendations for linguistic annotation released so far, such as those developed within the EAGLES and the SIMPLE European projects or by the ISO/TC 37 committee:
− As far as morphosyntactic annotations are concerned, OntoTag’s ontologies formalise the terms in the EAGLES (1996a) recommendations and their corresponding terms within the ISO Morphosyntactic Annotation Framework (ISO/MAF, 2008) standard;
− As for syntactic annotations, OntoTag’s ontologies incorporate the terms in the EAGLES (1996b) recommendations and their corresponding terms within the ISO Syntactic Annotation Framework (ISO/SynAF, 2010) standard draft;
− Regarding semantic annotations, OntoTag’s ontologies generalise and extend the recommendations in EAGLES (1996a; 1996b) and, since no stable standards or standard drafts have been released for semantic annotation by ISO/TC 37 yet, they incorporate the terms in SIMPLE (2000) instead;
− The terms coming from all these recommendations and standards were supplemented by those within the ISO Data Category Registry (ISO/DCR, 2008) and also of the ISO Linguistic Annotation Framework (ISO/LAF, 2009) standard draft when developing OntoTag’s ontologies.
Third, we showed that the combination of the results of tools annotating at the same level can yield better results (both in precision and in recall) than each tool separately. In particular,
1. OntoTagger clearly outperformed two of the tools integrated into its configuration, namely DataLexica and FDG in all the combination sub-phases in which they overlapped (i.e. POS tagging, lemma annotation and morphological feature annotation). As far as the remaining tool is concerned, i.e. LACELL’s tagger, it was also outperformed by OntoTagger in POS tagging and lemma annotation, and it did not behave better than OntoTagger in the morphological feature annotation layer.
2. As an immediate result, this implies that
a) This type of combination architecture configurations can be applied in order to improve significantly the accuracy of linguistic annotations; and
b) Concerning the morphosyntactic level, this could be regarded as a way of constructing more robust and more accurate POS tagging systems.
Fourth, Semantic Web annotations are usually pe
F. M. Pareja. La Religiosidad Musulmana
No full textVajda Georges. F. M. Pareja. La Religiosidad Musulmana. In: Revue de l'histoire des religions, tome 191, n°2, 1977. p. 224
POTENTIAL DIVIDENDS AND ACTUAL CASH FLOWS IN EQUITY VALUATION. A CRITICAL ANALYSIS
No full textPractitioners and most academics in valuation include changes in liquid assets (potential dividends) in the cash flows. This widespread and wrong practice is inconsistent with basic finance theory. We present economic, theoretical, and empirical arguments to support the thesis. Economic arguments underline that only flows of cash should be considered for valuation; theoretical arguments show how potential dividends lead to contradiction and to arbitrage losses. Empirical arguments, from recent studies, suggest that investors discount potential dividends with high discount rates, which means thatchanges in liquid assets are not value drivers. Hence, when valuing cash flows, we should consider only actual payments.Cash flow to equity, potential dividends, equity value.
Patente franciscano confirmando a Fr. Francisco Pareja como custodio de la Florida, 1607 mayo 11
No full textPatente que el Padre Comisario General de la Nueva España de los Frailes Menores de San Francisco envió a los frailes de la Custodia de Florida confirmando a Fr. Francisco Pareja como su custodio. —— Patent that the Father General Commissioner of the New Spain of the Friars Minor of San Francisco sent to the friars in the Custody of Florida confirming Fr. Francisco Pareja as custodian. 2 f. (4 p.
La violencia en la pareja
No full textEn el presente artículo se describen las variables que están relacionadas con las distintas formas de violencia en la pareja. Estas variables se han organizado en un modelo teórico que tiene en cuenta los factores culturales, las características sociodemográficas y familiares, las actitudes y otras variables definidas como inhibidores y facilitadores de la violencia en situaciones de conflicto. Se entrevistó a una muestra representativa de 10821 personas en las ocho ciudades del proyecto ACTIVA y se tuvieron en cuenta las respuestas de las 6184 que habían convivido en un enlace formal (matrimonio) o de unión no reglada o libre durante el año anterior a la entrevista. Los datos se obtuvieron a partir de las respuestas verbales a un cuestionario completado en el domicilio familiar de los entrevistados. Las variables que tuvieron una asociación clara con la violencia conyugal fueron: el nivel socioeconómico (a menos recursos, más violencia), el sexo (las mujeres tendían a maximizar la violencia y los varones a minimizarla, aunque el nivel de violencia fue similar), la edad (más violencia en los jóvenes), el estado civil (más violencia entre los no casados), la experiencia de malos tratos en la infancia (los más maltratados), el consumo excesivo de alcohol (los que se han embriagado), los que tenían actitudes de justificación de la violencia y los que tenían menos habilidades para enfrentarse a los conflictos. Los actos de violencia, que se dan de forma bidireccional en la pareja, tienen su origen en los procesos de socialización, tanto por la práctica de malos tratos, como por la transmisión de valores que se concretan en actitudes justificadoras de la violencia. El equilibrio de poder entre los miembros de la pareja, la modificación de las actitudes, la mejora de las habilidades para resolver conflictos y la reducción de los elementos estresantes pueden contribuir notablemente a reducir los niveles de violencia conyugal
La palabra de Dios en las Bienaventuranzas : sermones predicados en la Santa Iglesia Catedral de Madrid
No full textAntepPort. con orla tipA f. de lám. "Verba mea non praeteribunt. Matt., XXIV. 35
Representación social de pareja en hombres maltratados por su pareja
No full textEsta investigación busca explorar en un grupo de hombres la representación social de
pareja, partiendo de la caracterización de los mismos como sujetos victimas del
maltrato por parte de sus parejas, para ello se tuvieron en cuenta las manifestaciones
de maltrato del cual son victimas en su dinámica familiar y como estas se relacionan
con la configuración de pareja que estos han construido, se aplico una entrevista
semiestructurada la cual toma referencia de los antecedentes familiares de los sujetos,
la manifestaciones de maltrato y las representaciones sociales de pareja , los 3
sujetos fueron entrevistados en dos sesiones, y a través de su narrativa se
relacionaron las ideas recientes sobre la vida de los mismos teniendo en cuenta una
serie de ideas concretas, cotidianas y personales, las cuales se hicieron manifiestas
en la media en que los sentimientos, los pensamientos y las acciones se hicieron
presentes en la entrevistas, convirtiéndose ello en elementos intangibles los cuales a
través de las verbalizaciones de sus experiencias , la interpretación dada a este tipo
de manifestaciones permitió darle a estas una serie de significados comunes los
cuales se hacen presentes en la vidas de los sujetos, mostrando con ello grandes
diferencias en lo que para ellos es una pareja , su pareja ideal y las experiencias con
su pareja real.Abstract. – Introducción. -- 1. Justificación. -- 2. Marco conceptual y referencia bibliográfica. -- 2.1 Familia y Pareja. -- 2.2 Violencia Intrafamiliar. -- 2.3 Representaciones Sociales. -- 3. Planteamiento del problema. -- 4. Objetivos. -- 4.1 Objetivo General. -- 4.2 Objetivos Específicos. -- 5. Metodología. 5.1 Tipo de Estudio. -- 5.2 Caracterización de la población. - 5.3 Muestra. -- 5.4 Procedimiento. -- 5.5 Instrumento de recolección de información. -- 6. Presentación de los resultados. -- 7. Discusión. -- 8. Conclusiones. -- 9. Recomendaciones. -- 10. Bibliografía. -- Anexo
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