Exclusion Strategy Research Articles

UNDERSTANDING POLITICAL ISSUES THROUGH SOCIAL ACTORS REPRESENTATION:

Critical Discourse Analysis attempts to investigate social, political, historical and environmental issues by analyzing linguistic aspects and resources. This paper aims to examine the strategies used by journalists of tempo.co and CNN Indonesia in delivering the Governor of NTT’s school policy. Two research questions are formulated: (1) How the social actors are described in the news of Governor NTT’s policy publish in tempo.co and cnnindonesia.com. (2) What strategies used by tempo.co and cnnindonesia.com in describing the social actors of Governor NTT’s policy news. The results of the study indicate that the social actors are described in the news of Governor NTT’s policy publish in tempo.co and cnnindonesia.com by clearly mentioned the actors who responsible for the entry school policy. This educates the readers about the policy. Even though the actors are clearly mentioned, there is no tendency to marginalize them, especially Governor of NTT. By covering all person in charge, the readers are presented proportional news. Strategies used by tempo.co and cnnindonesia.com in describing the social actors of Governor NTT’s policy news is only inclusion strategy. Meanwhile, exclusion strategy is not detected in both news by tempo.co and CNN Indonesia.

Clinically oriented prediction of patient response to targeted and immunotherapies from the tumor transcriptome.

1553 Background: Precision oncology is gradually advancing into mainstream clinical practice, demonstrating significant survival benefits. However, eligibility and response rates remain limited in many cases, calling for better predictive biomarkers. Methods: We present ENLIGHT, a transcriptomics-based computational approach that identifies clinically relevant genetic interactions and uses them to predict a patient’s response to a variety of therapies in multiple cancer types, importantly, without training on previous treatment response data. Consequently, in addition to its ability to predict patients' response to approved and well-studied therapies, ENLIGHT can predict the response to new treatments in early development, even before clinical data has accumulated. Accordingly, we study ENLIGHT in two translationally relevant scenarios: Personalized Oncology (PO), aimed at prioritizing approved treatments to a given patient, and Clinical Trial Design (CTD), selecting the subset of most likely responders in a patient cohort. Results: Evaluating ENLIGHT’s performance on 21 blinded clinical trial datasets spanning 11 indications and 15 different drugs in the PO setting, we show that it can effectively predict a patient’s treatment response across multiple therapies and cancer types, with an overall odds ratio of 2.59 ( p=3.41e-8), and a 36% increase in response rate over the baseline ( p=3.30e-13). Its prediction accuracy is better than other state-of-the-art transcriptomics-based signatures. Unlike most signatures that are prognostic or provide insights for only very few, specific treatments, ENLIGHT provides matching scores to a broad range of treatments. Quite strikingly, its performance is comparable to that of supervised predictors developed for specific indications and drugs. In combination with the IFN-γ signature, ENLIGHT achieves an odds ratio larger than 4 in predicting response to immune checkpoint therapy. In the CTD scenario, our results show that by excluding non-responders ENLIGHT can enhance clinical trial success for immunotherapies and other monoclonal antibodies, achieving > 90% of the response rate attainable under an optimal exclusion strategy. Conclusions: ENLIGHT is a powerful transcriptomics-based precision oncology pipeline developed by Pangea Biomed that broadly predicts response to both extant and novel targeted and immune therapies, going beyond context-specific biomarkers.

Social exclusion with antisocial punishment in spatial public goods game

In the spatial public goods game (SPGG), social exclusion is an effective strategy to quickly promote group cooperation. However, the second-order free riding occurs among cooperators who do not bear additional exclusion costs in the process of exclusion. To ensure that the exclusion strategy works while solving the second-order free-riding problem, we introduce an antisocial punishment strategy. The model employs four counterbalancing strategies: pure cooperators invest into the public pool; the defectors are the first-order free-riders of the cooperators; the excluders restrict the defectors from riding the cooperators with a certain probability, and the excluded defectors cannot share the benefits of the common pool; and the antisocial punishers punish the cooperators. Through the Monte Carlo simulations, we found that the cooperative excluders protected the cooperators from invasion by defectors and defective punishers, and more importantly, the second-order free-riding problem of the system was eliminated by the defective punishers.

An adaptive dynamic multi-swarm particle swarm optimization with stagnation detection and spatial exclusion for solving continuous optimization problems

Particle swarm optimization (PSO) is a simple and efficient optimization method that has been used in many fields. However, PSO has some flaws including premature convergence and poor population diversity. To solve these problems of PSO, an adaptive dynamic multi-swarm particle swarm optimization with stagnation detection and spatial exclusion (ADPSO) is proposed. The newly proposed ADPSO is based on a dynamic multi-swarm PSO framework that cooperates with stagnation detection mechanism (SDM) and spatial exclusion strategy (SES). Firstly, the whole population is divided into multiple equal sub-swarms, which can be regrouped during evolution. The best particle of each sub-swarm, lbest, is used to evaluate the evolutionary state of each sub-swarm. If the lbest cannot improve its solution continuously without reaching the regroup period, the SDM will be triggered. In this case, a vitality particle is generated to help the stagnant sub-swarm to search for promising areas again. To keep the population diversity, the vitality particle is constructed according to the excellent historical information of all particles in the whole population. Secondly, to enhance the diversity of the population, the SES is proposed to avoid premature adsorption of all sub-swarms. Finally, the effect of ADPSO is evaluated using CEC2013, CEC2017 and four engineering optimization problems. The results shows that the proposed ADPSO is suitable for solving most optimization problems, and ADPSO has better results compared to the state-of-the-art PSO variants (i.e., MSCPSO, HCDMPS) and other popular evolutionary algorithms.

Abstract 957: Prediction of patient response to targeted and immunotherapies from the tumor transcriptome in a wide set of indications and clinical trials

Abstract Background: Precision oncology is gradually advancing into mainstream clinical practice, demonstrating significant survival benefits. However, eligibility and response rates remain limited in many cases, calling for better predictive biomarkers. Methods: We present ENLIGHT, a transcriptomics-based computational approach that identifies clinically relevant genetic interactions and uses them to predict a patient’s response to a variety of therapies in multiple cancer types, importantly, without training on previous treatment response data. Consequently, in addition to its ability to predict patients' response to approved and well-studied therapies, ENLIGHT can predict the response to new treatments in early development, even before clinical data has accumulated. Accordingly, we study ENLIGHT in two translationally relevant scenarios: Personalized Oncology (PO), aimed at prioritizing approved treatments to a given patient, and Clinical Trial Design (CTD), selecting the subset of most likely responders in a patient cohort. Results: Evaluating ENLIGHT’s performance on 21 blinded clinical trial datasets spanning 11 indications and 15 different drugs in the PO setting, we show that it can effectively predict a patient’s treatment response across multiple therapies and cancer types, with an overall odds ratio of 2.59 (p=3.41e-8), and a 36% increase in response rate over the baseline (p=3.30e-13). Its prediction accuracy is better than other state-of-the-art transcriptomics-based signatures. Unlike most signatures that are prognostic or provide insights for only very few, specific treatments, ENLIGHT provides matching scores to a broad range of treatments. Quite strikingly, its performance is comparable to that of supervised predictors developed for specific indications and drugs. In combination with the IFN-γ signature, ENLIGHT achieves an odds ratio larger than 4 in predicting response to immune checkpoint therapy. In the CTD scenario, our results show that by excluding non-responders ENLIGHT can enhance clinical trial success for immunotherapies and other monoclonal antibodies, achieving > 90% of the response rate attainable under an optimal exclusion strategy. Conclusion: ENLIGHT is a powerful transcriptomics-based precision oncology pipeline developed by Pangea Biomed that broadly predicts response to both extant and novel targeted and immune therapies, going beyond context-specific biomarkers. Citation Format: Gal Dinstag, Eldad D. Shulman, Efrat Elis, Doreen S. Ben-Zvi, Omer Tirosh, Eden Maimon, Isaac Meilijson, Emmanuel Elalouf, Boris Temkin, Philipp Vitkovsky, Eyal Schiff, Danh-Tai Hoang, Sanju Sinha, Nishanth Ulhas Nair, Joo Sang-Lee, Alejandro A. Schäffer, Ze'ev Ronai, Dejan Juric, Andrea B. Apolo, William L. Dahut, Stanley Lipkowitz, Raanan Berger, Razelle Kurzrock, Antonios Papanicolau-Sengos, Fatima Karzai, Mark R. Gilbert, Kenneth Aldape, Padma S. Rajagopal, Tuvik Beker, Eytan Ruppin, Ranit Aharonov. Prediction of patient response to targeted and immunotherapies from the tumor transcriptome in a wide set of indications and clinical trials [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 957.

Euclidean Distance Matrix-Based Rapid Fault Detection and Exclusion

<h3>Abstract</h3> Faulty signals from global navigation satellite systems (GNSSs) often lead to erroneous position estimates. A variety of fault detection and exclusion (FDE) methods have been proposed in prior research to both detect and exclude faulty measurements. This paper introduces a new technique for the FDE of GNSS measurements using Euclidean distance matrices. After a brief introduction to Euclidean distance matrices, both the detection and exclusion strategy is explained in detail. Euclidean distance matrix-based FDE is verified in two separate real-world data sets and proven to accurately detect and exclude GNSS faults on an average of 1.4-times faster than residual-based FDE and 70-times faster than solution separation FDE.

Exploiting the Sadness of Disabled Athletes

Reporting about athletes disables anything new in the world of journalism. In several regional, national, and international sports pages, journalists always write news about the other side of life and his struggles in overcoming disability in the match. It is interesting to see how athletes with disabilities are used as commodities and exploited their interests. So, with this view, the researcher analyzed a text entitled Exploitation of Sadness for Athletes with Disabilities (Theo Van Leeuwen's Critical Discourse Analysis on Detik.Com Edition January 16, 2022). The research uses Frankfurt’s critical theory, with qualitative methods, with a critical analysis approach from Theo Van Leeuwen. The results showed that the writer used several inclusion and exclusion strategies in the news text. The inclusion strategy focuses on Halil exploitation as the main star in the text above. Halil is described as a young man who has limitations and physical imperfections but wins in sports competitions. Meanwhile, in the exclusion strategy, the scriptwriter does not present a coach who has contributed to Halil's victory or a friend from a hawker association who is also an athlete who paved the way for Halil to become an athlete. With this inclusion and exclusion strategy, it can be seen how the perspective of news writers for persons with disabilities places them in an unequal position with humans in general

Clinically oriented prediction of patient response to targeted and immunotherapies from the tumor transcriptome

Precision oncology is gradually advancing into mainstream clinical practice, demonstrating significant survival benefits. However, eligibility and response rates remain limited in many cases, calling for better predictive biomarkers. We present ENLIGHT, a transcriptomics-based computational approach that identifies clinically relevant genetic interactions and uses them to predict a patient's response to a variety of therapies in multiple cancer types without training on previous treatment response data. We study ENLIGHT in two translationally oriented scenarios: personalized oncology (PO), aimed at prioritizing treatments for a single patient, and clinical trial design (CTD), selecting the most likely responders in a patient cohort. Evaluating ENLIGHT's performance on 21 blinded clinical trial datasets in the PO setting, we show that it can effectively predict a patient's treatment response across multiple therapies and cancer types. Its prediction accuracy is better than previously published transcriptomics-based signatures and is comparable with that of supervised predictors developed for specific indications and drugs. In combination with the interferon-γ signature, ENLIGHT achieves an odds ratio larger than 4 in predicting response to immune checkpoint therapy. In the CTD scenario, ENLIGHT can potentially enhance clinical trial success for immunotherapies and other monoclonal antibodies by excluding non-responders while overall achieving more than 90% of the response rate attainable under an optimal exclusion strategy. ENLIGHT demonstrably enhances the ability to predict therapeutic response across multiple cancer types from the bulk tumor transcriptome. This research was supported in part by the Intramural Research Program, NIH and by the Israeli Innovation Authority.

Nonparametric estimation-based five-layer neural network RAIM with improved availability

The monitoring performance of receiver autonomous integrity monitoring (RAIM) is restricted when visible satellites are limited in challenging environments. For that, artificial neural network-based RAIM methods have been investigated to improve the detection efficacy. Nevertheless, their corresponding fault exclusion and protection level algorithms are hardly provided for integrity assessments. In this regard, a nonparametric estimation-based RAIM method (NE-RAIM) is investigated to support fault detection, exclusion, and protection level calculation in this paper, boosting the declined monitoring capacity caused by the decrease of visible satellites. We propose a classification variable and a dynamic sampling method based on the variance inflation theory and then obtain the regression of the classification variable using nonparametric estimation. In this way, a five-layer NE-RAIM neural network is constructed to enhance the detection capability further. We also provide a NE-RAIM-based fault exclusion strategy by analyzing the detection result vector. Meanwhile, a protection level algorithm is proposed to enable direct integrity and availability evaluation based on searching the worst-case scenario where the missed detection risk is maximized. Results show that NE-RAIM requires a minimum pseudorange bias of 35 m to realize 100% detection rates under all single-faulty-satellite modes. Compared with least-square RAIM and advanced RAIM, NE-RAIM improves overall 24 h availability by 59.30% and 4.52%, respectively.

The Effects of Power on Consumer Decision Strategies: The Mediating Role of Behavioral Approach-Inhibition Tendency and the Moderating Role of Gender.

Previous studies on consumer decision strategies have focused on the process or outcomes of decision-making using different decision strategies. Relatively little is known about the factors (especially decision makers' characteristics) influencing the use of different decision strategies. This study examined the effects of power on consumer decision strategies and the underlying mechanisms. Studies 1 (N = 128) and 2 (N = 130) examined multiple- and binary-option situations, respectively. Participants' power was manipulated with a writing task and their consumer decision strategies were assessed through the selection tasks of restaurants and beach resorts. Study 3 (N = 326) further explored the mediator of approach-inhibition tendency and the moderator of gender in the relationship between power and consumer decision strategies. Participants' chronic sense of power, approach-inhibition tendency, and purchasing strategies were measured using questionnaires. Powerful (vs powerless) individuals prefer to use a direct selection (vs exclusion) strategy, regardless of whether they face multiple or binary choices. An increased approach (vs inhibition) tendency explains why elevated power promotes the use of the direct selection strategy. Moreover, gender plays a moderating role. Specifically, the mediation effect of approach (vs inhibition) tendency on the relationship between power and the preference for the direct selection (vs exclusion) strategy is stronger for males than for females. This study extends previous research on power and consumer decision strategies by clarifying that the effects of power on consumer decision strategies are primarily driven by high power (but not by low power). Furthermore, by examining the mediator of approach-inhibition tendency and the moderator of gender, this study promotes a deeper understanding of how power affects consumer decision strategies and for whom the effect is more salient. Besides, the present research has contributions to the approach-inhibition theory of power and the literature on gender differences in consumer behavior, and has practical implications for business marketing.

Improved Sliding Algorithm for Generating No-Fit Polygon in the 2D Irregular Packing Problem

This paper introduces an efficient and robust sliding algorithm for the creation of no-fit polygons. The improved algorithm can cope with complex cases and is given an implementation in detail. The proposed concept of a touching group can simplify the judging process when recognizing the potential translation vector for an orbital polygon. In addition, the generation of the no-fit polygon only involves three main steps based on the proposed concept. The proposed algorithm has a mechanism that searches other start positions to generate a complete no-fit polygon for handling complex cases. To improve the efficiency, many acceleration strategies have been proposed, such as point exclusion strategy and point inclusion test. The robust and efficient performance of the algorithm is tested by well-known benchmark instances and degenerate and complex cases, such as holes, interlocking concavities and jigsaw-type pieces. Experimental results show that the proposed algorithm can produce complete no-fit polygons for complex cases, and acceleration strategies can reduce the creation time of no-fit polygon on benchmark instances by more than sixteen percent on average.

Concentration and mobility of trace elements (Li, Ba, Sr, Ag, Hg, B) and macronutrients (Ca, Mg, K) in soil-orchid system on different bedrock types.

The mobility of chemical elements in the soil-orchid system has been poorly studied. The aim of this study is to evaluate the uptake and mobility of several trace (Li, Ba, Sr, Ag, Hg, and B) and macronutrients (Ca, Mg, and K) in the orchid Anacamptis morio (L.) R.M.Bateman, Pridgeon & M.W.Chase from soils in western Serbia. The sampling sites are characterized by three different bedrock types-cherts, limestones, and serpentines, which are the source of the significant chemical differences in the elemental status of the soil and plant tissues. The four-step Community Bureau of Reference sequential extraction procedure was used to determine the distribution of fractions and predict their potential phytoavailability. The orchid and soil samples were analyzed for total elemental content analysis using ICP-OES. The greatest potential for plant availability was determined for Ba and Sr, representing about 80% of the total soil content. More than 40% of Li in the soils was found to be potentially phytoavailable. Significant correlations were found between the total content of Li, B, and Sr in soils. Between 38 and 60% of Li content and more than 80% of Ba and Sr content were determined to be potentially phytoavailable by sequential analysis. The highest bioconcentration factor (> 1) was determined in the case of B and Sr for all orchid organs, while translocation factor for Li was highest in tubers and leaves. The studied elements were mainly stored in tubers and roots, indicating the exclusion strategy of A. morio as a metal tolerance mechanism. The data obtained showed significant differences in metal content in soils and plants originating from sites with different parent materials, suggesting that bedrock type and associated soil properties are important factors that determine chemical element mobility and uptake.

ENLIGHT: Pancancer response prediction to targeted and immunotherapies via tumor transcriptomics.

e13556 Background: Precision oncology is gradually advancing into mainstream clinical practice. Despite the significant recent growth in the number of approved biomarkers for immune and targeted therapies, demonstrating significant survival benefits, eligibility and response rates remain limited in many cases, calling for better predictive biomarkers. Methods: We developed ENLIGHT - a transcriptomics-based computational platform that identifies and utilizes clinically relevant genetic interactions (GIs) to predict a patient’s response to cancer treatments. ENLIGHT markedly extends and improves upon SELECT, a previous GI-based framework for obtaining transcriptomics-based response biomarkers. In this study, we focus on three key translational aspects: (i) the number of drugs for which predictions can be obtained (ii) defining a biomarker-based test for Personalized Medicine (PM) that would identify favorable treatments for an individual; and (iii) Improving clinical trial design by excluding a sub-population of patients likely not to respond to the treatment. A key translational feature of the approach is that it does not require training on treatment response data. Thus, in addition to its ability to predict patients' response to approved and well-studied therapies, it can predict the response to new, unexplored treatments. Results: We first tested Enlight in the PM scenario, analyzing 21 patient cohorts from diverse indications, treated with a variety of targeted and immunotherapies. The ENLIGHT treatment matching score is associated with better response with an aggregate Odds Ratio (OR) of 2.59 (95% confidence interval [1.85, 3.55], p= 3.41 e-8). Applied to the WINTHER trial data, encompassing multiple indications and individualized treatments, ENLIGHT recommendations achieved a highly remarkable OR of 11.15 ([2.3, 54.5], p = 8 e-04), demonstrating ENLIGHT’s strong predictive power across a broad spectrum of treatments and cancer types. Second, using ENLIGHT to exclude patients from clinical trials increases the trial response rate, achieving more than 90% of the response rate attainable under an optimal exclusion strategy. Conclusions: ENLIGHT is a powerful transcriptomics-based precision oncology pipeline developed by Pangea Biomed that broadly predicts response to both extant and novel targeted and immune therapies in translationally oriented, clinical terms, going beyond case-specific biomarkers.

A Corpus–assisted Critical Discourse Analysis of Exclusion Strategies in Political Newspaper Articles: The March of Return in Gaza

This study examines if there is a favored linguistic exclusion strategy in Arabic and English newspaper articles reporting on the March of Return in Gaza and explores their potential impacts on the readers' minds. Ten newspaper articles were collected; five articles are in Arabic, each is from a different Arab country, while the others are the top-selling five newspapers in the UK. Data were analyzed by observing the linguistic structures and the representations of social actors from the CDA perspective adopted by Theo van Leeuwen and using two built corpora to calculate the frequencies of the exclusion linguistic structures found. The findings showed that Arabic and English newspaper articles used linguistic exclusion strategies differently to serve specific functions, such as: excluding the social actors involved in the case of the March of Return in Gaza, driving the reader's attention to the other social actor to view him as a victim or the party who abuses power, hiding or protecting the excluded social actor or driving the reader's attention to the event rather than the action.

STRATEGI PEMBERITAAN MEDIA ONLINE INDONESIA DALAM KASUS DEMONSTRASI RUU HIP (ANALISIS WACANA KRITIS THEO VAN LEEUWEEN)

This research aimedto describe the different points of view among the Indonesian national online media, namely Detiknews.com, Kompas.com, CNN Indonesia and Tempo.com and to describe the tendency of the online media's attitudes in constructing the Demonstration case of the RUU HIP. The exclusion strategy is used to see how actors are excluded or hidden in the news text. This exclusion and inclusion strategy looks at how the forms of language usage are used to recapture the meaning to the public. The data of this research were found from reporting on the demonstration case of the RUU HIP in July 2020 in online media Detiknews.com, Kompas.com, Tempo.com and CNN Indonesia during 15-16 July 2020. This research used a qualitative descriptive method with a critical discourse analysis by Theo Van Leeuwen in order to describe how events and actors are portrayed in the news. The results showed that the form of Leeuwen's exclusion theory found in four news reports in online media was that Detiknews.com, Kompas.com, and CNN Indonesia in the news about the demonstration of the RUU HIP tended to use an inclusion strategy while, Tempo.com was more towards exclusion

Concentration and translocation of trace metals in Solidago gigantea in urban areas: a potential bioindicator

Invasive species usually grow in human-disturbed habitats including urban areas where they face numerous pollutants, including metals that attract special attention due to their non-degradability and high accumulation potential. In this study we evaluated the contents of potentially toxic metals (Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn) in the invasive species Solidago gigantea. The strategy adopted by S. gigantea in response to excess trace metals in the soil was assessed. Metal contents were determined using atomic absorption spectrometry in leaves, stems and roots of S. gigantea collected from 30 sites located in areas affected by various human activities. Metal concentrations (total and bioavailable fraction) were also determined in corresponding soil samples. Results showed that S. gigantea was able to inhabit strongly polluted sites. High Bioaccumulation Factor but low Translocation Factor values for Cd, Cu, Cr, Fe, Ni show that S. gigantea takes up metals from soil but reduces their transport to the aboveground parts and could be classified as a metal-tolerant species with exclusion strategy. The Bioaccumulation Factor values for Cd, Cu, Cr, Pb and Zn were remarkably higher in plants growing in areas characterized by low metal concentrations in soil compared to the ones affected by industry, with high metal concentrations. This suggests that S. gigantea that grows in polluted areas can reduce the uptake of potentially toxic metals. Regardless of the limited transport of metals to the aboveground organs, the content of metals in S. gigantea leaves differed between areas differing in human impact and the species can be used as a biomonitor.

Wacana Bukan Muhrim Pada Tayangan Video Cokro TV (Sebuah Analisis Wacana Kritis)

The speaker on Cokro TV's Youtube video, Ade Armando, expressed his opinion about the discourse of non-mahram which has invited controversy. The discourse of non-muhrim has sparked debate because it is associated with social problems that occur in society, namely choosing a doctor who is adjusted to the gender of the patient. This research emphasizes more on the ideology that the speaker wants to convey and the strategies used by the speaker to express his ideology. The critical analysis model used in this research is Van Leeuwen's critical analysis model. This research model is used to determine the social actors supported and marginalized by the speaker. This research uses a qualitative research approach with content analysis method. The results showed that the speakers used exclusion and inclusion strategies. The exclusion strategy used by the speaker leads to a passive discourse strategy, while the inclusion strategy used by the speaker leads to an identification discourse strategy.

Wacana Bukan Muhrim Pada Tayangan Video Cokro TV (Sebuah Analisis Wacana Kritis)

The speaker on Cokro TV's Youtube video, Ade Armando, expressed his opinion about the discourse of non-mahram which has invited controversy. The discourse of non-muhrim has sparked debate because it is associated with social problems that occur in society, namely choosing a doctor who is adjusted to the gender of the patient. This research emphasizes more on the ideology that the speaker wants to convey and the strategies used by the speaker to express his ideology. The critical analysis model used in this research is Van Leeuwen's critical analysis model. This research model is used to determine the social actors supported and marginalized by the speaker. This research uses a qualitative research approach with content analysis method. The results showed that the speakers used exclusion and inclusion strategies. The exclusion strategy used by the speaker leads to a passive discourse strategy, while the inclusion strategy used by the speaker leads to an identification discourse strategy.

“НІЧОГО НОВОГО”: ЩЕ РАЗ ПРО НЕМОЖЛИВІСТЬ ГЛОБАЛЬНОЇ ІСТОРІЇ МИСТЕЦТВА (коментарі до “Короткої книжки про мистецтво” Дани Арнольд)

I started this text as a review of another ‘short history of art’ that I came across. ‘A Short Book About Art’, written by the British art historian Dana Arnold, is a great example of the popularization and practical application of new approaches to art history. Among them are sociology, psychology of art, political iconology, gender art history and more. The researcher set an ambitious goal. The work is dedicated to finding common threads that connect the art of different geographical areas and demonstrate that the art of any period works in a similar way. We are talking, as we see, about the global history of the arts. This story should cover all regions and give a balanced representation of the cultures/arts of the different regions. However, the noble goal, as a careful reading of the work showed, not only did not solve the problem but also exacerbated it. Non-European art is almost ignored. In addition, the researcher builds a typical pro-Western narrative, where, however, the progressive approach is replaced by values. If progressivism was the ‘dark side of modernity’, the ‘value approach’ involves the consideration of non-European art exclusively from the perspective of Occidental values. Non-European art enters the narrative of global art history through hybridization due to glocalization. At the same time, the glocalization of art occurs in two ways. The first of them is passive. The projective vision of the researcher formed by Western values ​​simply does not notice and does not anticipate any difference between the ‘other’. Because of this, neither the ‘other nor its differences fall into the field of study. The second way of glocalization is active. It involves the relocation and recontextualization of culture. It is about moving culture in a familiar, acceptable to the researcher context (most often it is the morphology of art, topic or phenomenology). Both options for glocalization involve the implementation of an exclusion strategy, which makes it impossible to talk about global art history. Global art history is possible only as a result of non-trivial decolonial optics. However, decolonization as a postmodern project contradicts the modern idea of ​‘short history’ and centrifugal narrative.

Electoral discourse: women as represented by Russian and Colombian mass media

The authors analyse the linguistic strategies modern mass media use when writing about female politicians. Comparison of media discourses in Colombian and Russian media is made by means of interpretive, contextual. discourse and content analysis. The main aim of the study is to identify how the mass media view the role of women in politics and to what extent it is affected by the culture and mentality of the society of a given country. Based on Western European research, three linguistic strategies used by the mass media in the field of “women in politics” were dealt with. As a result of comparing Russian and Columbian media discourses the intensive use of these three strategies in the mass media discourse was identified. Exclusion strategy means that the political power that women have is delegated to them (by men). Invisibility strategy implies the use of a metaphor or catachreza (trope or stylistic error, incorrect or unusual use of word combinations with incompatible literal lexical meanings). The presence of a man as the main co-hero is a determining factor or an integral reference to the political activities of women. Caricature strategy implies description of political actions of women satirically, as caricature, as a ridiculous imitation. Ridicule, derogatory forms of address (derived from one's own name or a diminutive form of a name, reflecting the logic of underestimation) lead to a decline in status. The current media discourse broadcasts the idea that women in politics are isolated cases, exceptions, explained primarily by their personal, political or professional relations with men. Descriptions of women's political activities is full of with stereotypes, prejudices and preconceived notions. Colombian media discourse shows a steady trend towards the use of puns in the linguistic representation of women politicians while Russian mass media tend to use caricature strategies in positioning women in politics. The media discourse of both countries predominantly views women as actors in politics, as subjects that, by their very nature, cannot belong to politics.