bluuebunny/crossref_metadata_2025 huggingface dataset:
Multidimensional Variation of Ethical Constructs in VKontakte's Social Network Topologies
Authors: Horan Tyler
Published: September 2023

This study illuminates the role of cultural and personal values in shaping connections within online social networks, employing cross-cultural analysis and computational social science. By examining data from eight countries, the investigation underscores how political views, relationship status, and personal priorities significantly influence the number of connections within these networks. Results extend prior research by demonstrating the impact of a broader spectrum of values on network connections. Moreover, the findings show that the relationship between values and network connections varies across cultural contexts, emphasizing the importance of cross-cultural analysis in a globalized world. This study illustrates the potential of computational social science and big data approaches in elucidating complex social phenomena, particularly in understanding the structure of online social networks in the digital age. The findings highlight the necessity of interdisciplinary collaborations between computer science and social science in expanding our comprehension of the digital social world.
A time of decline: an eco-anthropological and ethnohistorical investigation of mpox in the Central African Republic
Authors: Duda Romain , Betoulet Martial José , Besombes Camille , Mbrenga Festus , Borzykh Yanina , Nakoune Emmanuel , Giles-Vernick Tamara
Published: September 2023

The Central African Republic (CAR) has experienced repeated mpox outbreaks since 2001. Although several mpox epidemiological risk factors for zoonotic and interhuman transmission have been documented, the reasons for more frequent epidemic outbreaks are less well understood, relying on vague explanatory categories, including deforestation, hunting, and civil unrest. To gain insight into increasingly frequent outbreaks, we undertook a mixed methods ethnohistorical, eco-anthropological analysis in two CAR regions: the Lobaye, experiencing one or more annual outbreaks in the past decade, and the Sangha-Mbaere, with a longer-term history but less frequent outbreaks. We comparatively examined changing political economies, forest use practices, and understandings of mpox. In 2022, we conducted 40 qualitative ethnohistorical, anthropological interviews in Sango and French and conducted participant-observation of forest activities. For comparative purposes, we also drew on intensive field research conducted in one of these sites, consisting of participant-observation and a database of historical data on hunting, trapping, and meat consumption collected over 6 months in 1993. We find increased rodent capture and consumption in both sites in the past 30 years, and expanded practices of other potentially risky activities. We also find important differences in risky practices between the Lobaye and Sangha-Mbaere participants. Significantly, Lobaye and Sangha participants underscored historical processes of decline producing mpox among other emergences but they framed these declension processes diversely as economic, political, nutritional, and moral. Our findings are important because they mobilize new types of evidence to shed light on the processual dynamics of mpox outbreaks in the CAR. This study also reveals variability across two sites within the same country, highlighting the importance of comparative, fine-grained anthropological and historical research to identify underlying dynamics of mpox outbreaks. Finally, our study points to the need for mpox interventions and risk communication accounting for these regional differences, even within a single country.
Większość arytmetyczna czy konkurencyjna?Konstytucja Stanów Zjednoczonych w myśli politycznej Johna Caldwella Calhouna
Authors: Tulejski Tomasz
Published: September 2023

John Caldwell Calhoun was an American statesman and political theorist from South Carolina who defended the interest of the Union southern states. Calhoun was one of staunch spokesmen of slavery, but in this article the author presents his constitutional and political thought. After the introduction of the Tariff of Abominations Calhoun became one of the most important actors in the nullification crisis and a defender of states’ rights, limited federal government and the right to nullify. Referring to the ideas of the Founding Fathers, Calhoun considered the Union as a union of sovereign states and he opposed the strengthening of the federal government. He rejected numerical democracy and advocated the introduction of a constitutional reform protecting minority from the tyranny of majority. He proposed the concept of a concurent majority, which took into account various interests and, consequently, defended the agricultural South from the industrial domination of the North. His reflections and warnings heavily influenced the South’s secession and the outbreak of the Civil War.
Determination of Earnings Quality and Firm Value: New Evidence from Indonesian Non-financial Companies
Authors: . Ellin , Erna Wati
Published: September 2023

This research aims to determine the factors affecting earnings quality and firm value empirically. Two theories underlie the conceptual framework of this research, namely agency theory and signaling theory. Agency conflicts arise due to conflicts of interest and information asymmetry between principals as users of information and agents as providers of information. Then, the emergence of signal theory acts as a moral reason for companies to send signals to the market to reduce information asymmetry between agents and principals by reporting on the company's operating and financial performance. The statistical population of this research consists of all non-financial companies listed on the Indonesia Stock Exchange covering the period of 2017-2020, giving 1.735 and 1.727 observations data for each dependent variable. This study employs multiple linear regression methods to test and analyze the data. The findings show a significant relationship between growth, Earnings Quality (EQ), and Firm Value (FV). Firm size, cash to current assets, current debt to total assets, listing age, market capitalization, and earnings management have no significant influence on EQ but significant on FV. The managerial capability only has a significant impact on EQ. Furthermore, the working capital ratio, earnings per share, firm age, price earnings ratio, and CSR award do not affect EQ and FV. The novelty of this research is to acumen the best factor affecting earnings quality and firm value.
Sharpening the Concept of Tax Literacy as an Effort to Improve Tax Compliance
Authors: Tantriangela Jessy , Setyowati Milla Sepliana
Published: September 2023

The self-assessment system used by many countries raises the issue of non-compliance in the taxation sector. With this, tax literacy is believed to be able to increase tax compliance. Unfortunately,  studies that specifically study tax literacy are still rarely found. This article aims to sharpen the existing concept of tax literacy, especially in the context of raising tax compliance. This article uses a qualitative method, where the researcher summarizes and presents the condition of the knowledge of tax literacy to this day. In this article, the researcher sharpens three dimensions of tax literacy. First, tax literacy is related to the taxation knowledge of the taxpayers, namely general, procedural, and legal knowledge. Second, tax literacy is related to the taxpayers’ personal values, which is related to their interest in reading about taxation. Third, tax literacy is also related to the social values of taxpayers, which is related to the service provided by tax authorities to taxpayers, specifically in providing the ease of tax administration. With this article, hopefully, the tax authorities–especially in developing countries–will pay more attention to the important issue of tax literacy so that they can design efficient policies in an effort to increase tax compliance.
Investigating the association between Veteran status and rate of emergency department visits
Authors: Saunders James , St. Cyr Kate , Cramm Heidi , Aiken Alice B. , Kurdyak Paul , Sutradhar Rinku , Mahar Alyson L.
Published: September 2023

LAY SUMMARY

How Veterans use the emergency department (ED) after they leave the military could signal unmet health needs or health crises. Describing patterns of ED use could inform health policy to better support Veterans during military service or design programs and services for them after they leave. ED visit records from Ontario were used to compare how often Veterans and non-Veterans visited the ED. How often a Veteran went to the ED, and how that rate compared with that of non-Veterans, depended on how long the Veteran served in the military and whether they were male or female. For example, Veterans with less than 5 or with 5–9 years of service had a higher rate of ED visits relative to non-Veterans, whereas those who served for 20–29 or for 30 years or more had a lower rate of ED visits. An understanding of how to design health services and programs for female Veterans, and for those serving shorter durations, is needed.
Impacts of online education during COVID-19 on teaching English in rural state schools in Türkiye
Authors: ÇAKIR İsmail , BAYHAN Serap
Published: September 2023

It is a commonly experienced fact that teaching English as a foreign language in rural areas is challenging for language teachers around the world. This study explored the actual challenges that teachers of English faced at rural state schools before and during COVID-19. To find out the regarding problems, an open-ended questionnaire was administered to 46 participants working at public schools as teachers of English in different regions of Türkiye. Additionally, to have a deeper understanding of the challenges that teachers of English faced during COVID-19 period, the reports from the focused group discussions were analyzed using content analysis. The discussions were held by 29 teachers of English working in the same rural district. The results revealed that teachers had some common difficulties deriving from school facilities, poor infrastructure, inadequate technology, instructional materials, students’ language levels, attitudes towards language learning and teacher competencies. The study also shed light on the positive impacts of the online education on teaching English as a foreign language in rural areas during COVID-19 pandemic in relation with the technological challenges and its effect on decreasing the urban-rural divide.
Evaluation of digital instructional materials developed by primary school teacher candidates with different learning styles
Authors: TATLI Zeynep , GÜLAY Ahmet , MURADOĞLU Bahar , BEKAR Şeyma Nur
Published: September 2023

This embedded design mixed-method study aimed to evaluate the teaching materials developed by primary school teacher candidates using Web 2.0 tools in line with their learning styles. The participants comprised 60 primary school teacher candidates identified via purposive sampling. The data were collected with the Maggie McVay Lynch Learning Style Inventory and the Digital Teaching Material Development Self-Efficacy Scale, and from the products of the primary school teacher candidates. Inventory data were subjected to descriptive statistics, the product data were subjected to descriptive analysis and the scale data were subjected to the paired sample t-test of inferential statistics techniques. The results indicated that the majority of the primary school teacher candidates had visual learning styles and used Kahoot and LearningApps Web 2.0 tools for measurement-evaluation and Canva and Emaze for presentation purposes. In addition, the material development process according to learning styles significantly increased the participants' self-efficacy in developing digital teaching materials. Based on these results, it was suggested to determine the learning styles of teacher candidates to develop teaching materials accordingly.
Małgorzata Ganczar, Alicja Sytek, Informatyzacja administracji publicznej. Skuteczność regulacji, Wydawnictwo CeDeWu, Warszawa 2021
Authors: Barczewska-Dziobek Agata
Published: September 2023

Recenzja książki: Małgorzata Ganczar, Alicja Sytek, Informatyzacja administracji publicznej. Skutecznośćregulacji, Wydawnictwo CeDeWu, Warszawa 2021, ss. 298.
Trust BUT VERIFY: Maintaining Research Integrity in the 21st Century
Authors: Brown Scott W
Published: September 2023

Research misconduct erodes the trust of the stake holders in the social science research enterprise. In order to return confidence and trust in social science research findings, we must emphasize research integrity through education and transparency. This essay discusses three fundamental components of research misconduct to raise awareness of examples of fabrication and falsification misconduct by several prominent social science researchers.
CURRENT PROBLEMS OF IMPLEMENTING INCLUSIVE EDUCATION IN EDUCATIONAL INSTITUTIONS OF UKRAINE AND COUNTRIES OF THE EUROPEAN UNION
Authors: HRYSHCHENKO SVITLANA
Published: September 2023

The article analyzes current problems of implementing inclusive education in educational institutions of Ukraine and countries of the European Union. Various specific aspects of inclusive education in European countries are highlighted. It is substantiated that there is a need to stimulate the use of the best world experience in the implementation of inclusive education in different countries. An important aspect is ensuring effective investment into inclusive education both in Ukraine and in the countries of the European Union.

The purpose of the article is to analyze the experience of implementing inclusive education in the countries of the European Union and Ukraine.

It is defined that the implementation of inclusive education in Ukrainian educational system has a number of urgent problems that must be solved, namely: the lack of a clear mechanism for the implementation of inclusive education; the lack of a unified approach to understanding the terms used in the process of obtaining an education by people with special educational needs; the need to introduce inclusive education at all levels of education in Ukraine; different sub-departments of educational institutions (special and general); the need to review the mechanism of state financing of educational institutions that provide inclusive educational services; introduction of broad educational work among the population regarding the necessity and positive nature of the implementation of inclusive education.

Current problems of inclusive education in the European Union are as follows: increasing the quality and significance of inclusive education; increasing the number of graduates and reducing the number of people who do not graduate from educational institutions; review and preparation of educational programs that will meet the needs of people with special educational needs in education; stimulating the use of world leading experience in teaching and scientific research; providing higher education students with wider opportunities to acquire additional skills through study and internships abroad; strengthening links between inclusive education, research and business; ensuring effective investment into inclusive education.
LEGISLATIVE SUPPORT FOR HIGHER EDUCATION IN AUSTRALIA
Authors: BARANOVSKA LILIYA , ZHURAVEL NATALIIA
Published: September 2023

The article examines and analyses legislative support of higher education in Australia and compares it with the educational legislation of Ukraine. It is defined that Australia is a federal country and its education legislation is provided by the National and State Governments. The national government develops the national education policy and substantiates its guiding principles. The federal government is responsible for funding higher education and provides additional funding to the states. State and territory governments control all aspects of education except universities. The laws in this country are effective. In education, they are focused on improving the quality of professional training, forming such competences of higher education students that employers expect and that are appropriate for workplaces. Higher education in Australia is provided by universities and colleges, as well as institutions of the state-controlled TAFE (Technical and Further Education) system. Universities in Australia provide theoretical training for higher education applicants. Vocational education, focused on the development of specific skills for activities in a specific workplace, is provided by TAFE institutions. Their programmes are developed in partnership with business and industry communities.

In addition to the public TAFE system, there are also private vocational colleges. The legislative framework of higher education in Australia includes: Australian Education Act, Higher Education Act, Higher Education Support Act, Australian Qualifications Framework, Training Packages.

The latter outline the standards of professional skills that can be used to train and assess the competences of education seekers. Training Packages were developed in the process of national consultations with industry. Their goals are to determine the match between the demand for qualifications and the supply; encourage the development of a flexible and relevant workforce and training; ensure national recognition of professional and technical training results; support people in the choice of education and career.
THE EFFECT OF COMPENSATION AND WORKLOAD ON EMPLOYEE PERFORMANCE WITH TURNOVER INTENTION AS A MEDIATION VARIABLE IN SAVE THE CHILDREN INDONESIA
Authors: Kurwiany Kurwiany , Emmanuel Bay Dhirgantara
Published: September 2023

This study is intended to prove the effect of compensation and workload on turnover intention at Save the Children Indonesia. To find out and analyze the effect of compensation, workload and turnover intention on the performance of Save the Children Indonesia. To prove and analyze the effect of compensation and workload on performance with turnover intention as a mediating variable at Save the Children Indonesia. The population in this study were all 303 employees of Save the Children Indonesia, the probability sampling method was used as a sample and the sampling technique used simple random sampling, the sample amounted to 91 employees at Save the Children. Indonesian children. The analysis data method SEM with the help of the SmartPLS version 3.2.9 program. The results of this study found that compensation has a significant negative effect on turnover intention at Save the Children Indonesia. Workload has a significant negative effect on turnover intention at Save the Children Indonesia. Compensation has a significant positive effect on employee performance at Save the Children Indonesia. Workload has a positive and significant effect on employee performance at Save the Children Indonesia. Turnover intention has a negative and significant effect on the performance of Save the Children Indonesia employees. Compensation provides a positive and significant effect on employee performance mediated by turnover intention at Save the Children Indonesia. Workload has a positive and significant effect on employee performance mediated by turnover intention at Save the Children Indonesia.
THE IMPORTANCE OF COMPETENCE AND CAREER DEVELOPMENT TOWARDS EMPLOYEE PERFORMANCE IN MEDIATION OF MOTIVATION VARIABLES IN BI MONEY MANAGEMENT WORK UNITS (SATKER) IN JAVA ISLAND
Authors: Damara Sakti Deri , Deden Kurniawan
Published: September 2023

Basically, this study aims to examine and analyze the importance of competence and career development on employee performance by using the motivation variable as a mediating variable in the BI Money Management work unit in Java. By using a quantitative research design with an explanatory survey method , namely data collection using a questionnaire with a Likert scale model. The sample collection of organic employee respondent data is 300 respondents. Structural Equation Modeling (SEM) PLS Version 3.2.9 is used as a tool to process data. In this study using four variables, fourteen dimensions and thirty-six indicators. From the results of this study it can be concluded that all variables have a significant effect on employee performance, namely: 1) Competence on employee performance. 2) Career development on employee performance, 3) Motivation on employee performance, 4) Competence on motivation, 5) Career development on motivation, 6) Motivation mediates the effect of competence on employee performance, 7) Motivation mediates the effect of career development on employee performance.
ANALYSIS OF FINANCIAL DIGITALIZATION ON BUMDES AS A KNOWLEDGE-BASED VIEW PERSPECTIVE: (Case of Bumdes Bumirejo, Dampit, Malang Regency)
Authors: Kustiningsih Nanik
Published: September 2023

Research on knowledge management is centered on the question of how companies from small to large scale manage their assets, so that they can produce a comparative advantage. The times have forced economic actors to adapt in order to answer any existing challenges. The use of appropriate technology is a central issue in responding to the challenges that arise. Large companies have sufficient human resources to integrate technology with existing governance. However, this is not necessarily the case with small economic units such as Village Owned Enterprises (BUMDes). This study aims to explain how BUMDes manages the new knowledge gained, thereby contributing to increased performance (knowledge-based strategy). The method used is a qualitative research method with an exploratory approach. The process of data collection and analysis is divided into two stages. First, in-depth interviews with several predetermined samples. The results of the interviews were then analyzed to obtain preliminary results or the level of knowledge currently owned by BUMDes. The second stage is training and workshops for partners to introduce new types of knowledge, namely digital-based financial management. Furthermore, data collection was carried out through focus group discussions (FGD). The results of this study are the performance of BUMDes Bumirejo is increasing and contributing to the village economy, especially in the transparency of digital-based financial management. The main key. To achieve the desired hope is to improve the village economy. Trust, commitment and sustainability of BUMDes development.
Are smartphone buyers being rational?
Authors: Mulia Dipa , Muchsin Saggaff Shihab
Published: September 2023

This research is related to consumer behavior when purchasing a smartphone one of product that is closely related to technology. The purpose of this study is to determine marketing strategies by analyzing consumer behavior both rational aspect and emotional aspects. The independent variables represent rational aspect are technology, price perception, e-WoM, while emotional aspect represented by Emotion variable, and Trust is selected  as a mediator variable of rational aspect. As the dependent variable is the intention to buy a smartphone. This research is a quantitative research, the sample used in this study was taken by purposive sampling method with the criteria of the respondent is smartphones users. The number of samples in this study is 338 respondents. The analysis used in the research uses structure equation modeling (SEM) to test the hypotheses in the proposed research model.
The Influence of Social Media Influencer and Electronic Word of Mouth Mediated By Brand Image on Purchase Intention at Eternamoore Beauty Clinic Makassar
Authors: Markiones Sartika Aprilia , Buyung Romadhoni  , Andi Mappatompo
Published: September 2023

This article investigates the effect between social media influencer and electronic word of mouth mediated by brand image on purchase intention at Eternamoore Beauty Clinic Makassar through descriptive-quantitative research. We test the hypotheses of 117 respondents from Eternamoore’s Instagram followers and used the Structural Equation Modelling with PLS. The result reveal that social media influencer exhibit better for brand image. Electronic word of mouth has significant and positive effect on brand image. Whereas the social media influencer has unsignificant effects on purchase intention, brand image mediates this effect. Electronic word of mouth can enhance purchase intention. Additionally, the moderated mediation analysis result revealed that the indirect effect of electronic word of mouth on purchase intention is positively moderated by brand image. These results provide a better understanding of the influencer and e-WOM and offer important contribution to the social media marketing and add valuable insights for practitioners to advance the use of Influencers and e-WOM.
MUTU PENDIDIKAN ISLAM: JENIS KESISTEMAN, KONSTRUKSI KESISTEMAN DAN BERFIKIR KESISTEMAN
Authors: Fardinal Fardinal , Ali Hapzi , Anwar US Kasful
Published: September 2023

Dalam meningkatkan Mutu Pendidikan Islam sangat di perlukan Perubahan dan usaha yang lebih baik lagi, di karenakan tantangangan zaman yang akan datang menuntut lembaga pendidikan islam untuk mengikuti perkembangan zamannya, untuk menumbuhkan kepercayaan dan minat masyarakat sangat perlu peningkatan Mutu pendidikan itu sendiri, agar anak anak yang mereka titipkan pada Lembaga pendidikan Islam mampu bersaing dan mampu mengahadapi era saat ini. Pendekatan sistem atau berpikir kesisteman adalah salah satu solusi mendasar yang harus dipahami dan diterapkan oleh setiap manajer lembaga pendidikan Islam agar Lembaga Pendidikan Islam menjadi Lembaga pendidikan yang bermutu. Artikel ini mereview Faktor-faktor yang mempengaruhi Mutu Pendidikan Islam, yaitu: Jenis Kesisteman, Konstruksi Kesisteman dan Berfikir Kesisteman, suatu studi literatur Manajemen Sumberdaya Manusia. Tujuan penulisan artikel ini guna membangun hipotesis pengaruh antar variabel untuk digunakan pada riset selanjutnya. Hasil artikel literature review ini adalah: 1) Jenis Kesisteman berpengaruh terhadap Mutu Pendidikan Islam; 2) Konstruksi Kesisteman berpengaruh terhadap Mutu Pendidikan Islam; dan 3) Berfikir Kesisteman   berpengaruh terhadap Mutu Pendidikan Islam.
Faktor-Faktor Yang Mempengaruhi Tingkat Deviasi Halaman III DIPA pada Satker Lingkup Kemenag Bangka Belitung
Authors: Arnida Arnida
Published: September 2023

Tujuan penulisan ini adalah untuk meneliti faktor-faktor yang mempengaruhi tingkat deviasi halaman III DIPA dengan studi penelitian pada satker lingkup kementerian agama provinsi Bangka Belitung. Penilaian kinerja atas pelaksanaan anggaran pada satuan kerja diukur melalui sebuah tool yang dinamakan Indikator Kinerja Pelaksanaan Anggaran (IKPA) yang menilai aspek perencanaan, pelaksanaan, dan aspek hasil. Indikator deviasi halaman III DIPA merupakan salah satu indikator pada aspek kualitas perencanaan anggaran. Pada tahun 2020 dan 2021, indikator deviasi halaman III DIPA menjadi indikator  yang selalu muncul sebagai salah satu indikator yang tidak mencapai target. Nilai pada indikator ini menunjukkan kualitas penyusunan perencanaan penarikan dana yang tertuang pada Halaman III DIPA yang disusun oleh satker . Dari sisi lain, kurang akuratnya rencana penarikan dana ini dapat mempengaruhi kredibilitas pemerintah dalam hal memenuhi ketersediaan dana  kas negara untuk keperluan belanja yang dibiayai oleh Anggaran Pendapatan Belanja Negara (APBN).
Pengaruh Return on Asset (ROA), Return on Equity (ROE), Net Profit Margin (NPM) dan Earning Per Share (EPS) terhadap Harga Saham (Suatu Kajian Studi Literatur Manajemen Keuangan Perusahan)
Authors: Hervita Nenobais Audrey , Sia Niha Simon , Manafe Henny A.
Published: September 2023

Penelitian terdahulu maupun Penelitian yang relevan sangat berguna terhadap suatu penelitian maupun kajian pustak suatu karya ilmiah baik mengkaji tentang pengaruh antar variabel maupun Faktor lain yang turut mempengaruhi suatu variabel itu sendiri. Artikel ini Membahas tentang suatu kajian pustaka faktor yang mempengaruhi harga saham, yakni return on asset (ROA), return on equity (ROE), net profit margin (NPM) maupun earning per share (EPS). Penulisan artikel ini bermaksud agar bisa menentukan hipotesis yang berdampak pada tiap variabel supaya mampu dimanfaatkan bagi penulisan artikel selanjutnya. Hasil riset ini, seperti: 1) Return on asset (ROA) berdampak positif maupun krusial bagi harga saham; 2) Return on equity (ROE) berdampak positif maupun krusial bagi harga saham; 3) Net profit margin berdampak positif maupun krusial bagi harga saham; 4) Earning per share (EPS) berdampak positif positif maupun krusial bagi harga saham; 5) ROA, ROE, NPM, dan EPS berdampak positif maupun krusial secara simultan bagi harga saham.
Pengaruh Disiplin Kerja, Motivasi Kerja dan Budaya Organisasi Melalui Kepuasan Kerja sebagai Variabel Mediasi terhadap Pengembangan Karir (Suatu Kajian Studi Literatur Manajemen Sumberdaya Manusia)
Authors: Dias Amaral Feodora , EHJ FoEh John , Man Stanis , Ayu Diah
Published: September 2023

Karya ilmiah ini mengulas mengenai kajian pustaka, terutama faktor yang berpengaruh kepada pengembangan karier: kepuasan kerja sebagai variabel intervening, serta disiplin kerja, motivasi kerja maupun budaya organisasi. Karya ilmiah ini peneliti tulis agar bisa menentukan hipotesis yang berpengaruh ke antarvariabel supaya bermanfaat bagi penulisan selanjutnya. Hasil yang didapat ialah disiplin kerja berakibat positif dan penting kepada pengembangan karir; motivasi kerja berakibat positif dan penting kepada pengembangan karir; budaya organisasi berakibat positif dan penting kepada pengembangan karir; disiplin kerja  berakibat positif dan penting kepada kepuasan kerja; motivasi kerja berakibat positif dan penting kepada kepuasan kerja; budaya organisasi berakibat positif dan penting kepada kepuasan kerja; dan kepuasan kerja mempengaruhi positif maupun krusial bagi pengembangan karir.
Fußball – eine Weltreligion im 21. Jahrhundert
Authors: Herzog Markwart
Published: September 2023

Der vorliegende Beitrag vertritt die These, dass Fußball eine Religion sei. Diese Auffassung teilt er beispielsweise mit den Historikern Nils Havemann (2013: 343–352) und Moshe Zimmermann (2014; vgl. Herzog 2014b). Zur Begründung der These ruft das erste Kapitel zunächst frühe Wortmeldungen in Erinnerung, die in diese Richtung weisen, unter anderem von Hans Seiffert, Siegfried Salomon und vor allem von Walther Bensemann. Nach einigen begriffsstrategischen Überlegungen werden neun Dimensionen untersucht, die in der Fußballreligion und anderen Religionen anzutreffen sind. Dabei geht es nicht um Analogien, sondern um Schnittmengen zwischen populärer und traditioneller Religion. Ein Resümee bringt diese Dimensionen auf den Nenner der Kontingenzbewältigung. Damit soll deutlich werden, dass Fußball zahlreiche Leistungen erbringt wie andere Religionen und deshalb mit guten Gründen zu diesen gezählt werden kann.
On Contrastive Explanations for Tree-Based Classifiers
Authors: Audemard Gilles , Lagniez Jean-Marie , Marquis Pierre , Szczepanski Nicolas
Published: September 2023

We define contrastive explanations that are suited to tree-based classifiers. In our framework, contrastive explanations are based on the set of (possibly non-independent) Boolean characteristics used by the classifier and are at least as general as contrastive explanations based on the set of characteristics of the instances considered at start. We investigate the computational complexity of computing contrastive explanations for Boolean classifiers (including tree-based ones), when the Boolean conditions used are not independent. Finally, we present and evaluate empirically an algorithm for computing minimum-size contrastive explanations for random forests.
Efficient Algorithms for Monroe and CC Rules in Multi-Winner Elections with (Nearly) Structured Preferences
Authors: Chen Jiehua , Hatschka Christian , Simola Sofia
Published: September 2023

We investigate winner determination for two popular proportional representation systems: the Monroe and Chamberlin-Courant (abbrv. CC) systems. Our study focuses on (nearly) single-peaked resp. single-crossing preferences. We show that for single-crossing approval preferences, winner determination of the Monroe rule is polynomial, and for both rules, winner determination mostly admits FPT algorithms with respect to the number of voters to delete to obtain single-peaked or single-crossing preferences. Our results answer some complexity questions from the literature [19, 29, 22].
On the Robustness of Split Learning Against Adversarial Attacks
Authors: Fan Mingyuan , Chen Cen , Wang Chengyu , Zhou Wenmeng , Huang Jun
Published: September 2023

Split learning enables collaborative deep learning model training while preserving data privacy and model security by avoiding direct sharing of raw data and model details (i.e., server and clients only hold partial sub-networks and exchange intermediate computations). However, existing research has mainly focused on examining its reliability for privacy protection, with little investigation into model security. Specifically, by exploring full models, attackers can launch adversarial attacks, and split learning can mitigate this severe threat by only disclosing part of models to untrusted servers. This paper aims to evaluate the robustness of split learning against adversarial attacks, particularly in the most challenging setting where untrusted servers only have access to the intermediate layers of the model. Existing adversarial attacks mostly focus on the centralized setting instead of the collaborative setting, thus, to better evaluate the robustness of split learning, we develop a tailored attack called SLADV, which comprises two stages: 1) shadow model training that addresses the issue of lacking part of the model and 2) local adversarial attack that produces adversarial examples to evaluate. The first stage only requires a few unlabeled non-IID data, and, in the second stage, SLADV perturbs the intermediate output of natural samples to craft the adversarial ones. The overall cost of the proposed attack process is relatively low, yet the empirical attack effectiveness is significantly high, demonstrating the surprising vulnerability of split learning to adversarial attacks.
Multi-Unit Auction over a Social Network
Authors: Fang Yuan , Zhang Mengxiao , Liu Jiamou , Khoussainov Bakh , Xiao Mingyu
Published: September 2023

Diffusion auction is an emerging business model where a seller aims to incentivise buyers in a social network to diffuse the auction information thereby attracting potential buyers. We focus on designing mechanisms for multi-unit diffusion auctions. Despite numerous attempts at this problem, existing mechanisms either fail to be incentive compatible (IC) or achieve only an unsatisfactory level of social welfare (SW). Here, we propose a novel graph exploration technique to realise multi-item diffusion auction. This technique ensures that potential competition among buyers stay “localised” so as to facilitate truthful bidding. Using this technique, we design multi-unit diffusion auction mechanisms MUDAN and MUDAN-m. Both mechanisms satisfy, among other properties, IC and 1/m-weak efficiency. We also show that they achieve optimal social welfare for the class of rewardless diffusion auctions. While MUDAN addresses the bottleneck case when each buyer demands only a single item, MUDAN-m handles the more general, multi-demand setting. We further demonstrate that these mechanisms achieve near-optimal social welfare through experiments.
Generalizing Similarity in Noisy Setups: The DIBS Phenomenon
Authors: Fonseca Nayara , Guidetti Veronica
Published: September 2023

This work uncovers an interplay among data density, noise, and the generalization ability in similarity learning. We consider Siamese Neural Networks (SNNs), which are the basic form of contrastive learning, and explore two types of noise that can impact SNNs, Pair Label Noise (PLN) and Single Label Noise (SLN). Our investigation reveals that SNNs exhibit double descent behaviour regardless of the training setup and that it is further exacerbated by noise. We demonstrate that the density of data pairs is crucial for generalization. When SNNs are trained on sparse datasets with the same amount of PLN or SLN, they exhibit comparable generalization properties. However, when using dense datasets, PLN cases generalize worse than SLN ones in the overparametrized region, leading to a phenomenon we call Density-Induced Break of Similarity (DIBS). In this regime, PLN similarity violation becomes macroscopical, corrupting the dataset to the point where complete interpolation cannot be achieved, regardless of the number of model parameters. Our analysis also delves into the correspondence between online optimization and offline generalization in similarity learning. The results show that this equivalence fails in the presence of label noise in all the scenarios considered.
Approximate Model-Based Shielding for Safe Reinforcement Learning
Authors: Goodall Alexander W. , Belardinelli Francesco
Published: September 2023

Reinforcement learning (RL) has shown great potential for solving complex tasks in a variety of domains. However, applying RL to safety-critical systems in the real-world is not easy as many algorithms are sample-inefficient and maximising the standard RL objective comes with no guarantees on worst-case performance. In this paper we propose approximate model-based shielding (AMBS), a principled look-ahead shielding algorithm for verifying the performance of learned RL policies w.r.t. a set of given safety constraints. Our algorithm differs from other shielding approaches in that it does not require prior knowledge of the safety-relevant dynamics of the system. We provide a strong theoretical justification for AMBS and demonstrate superior performance to other safety-aware approaches on a set of Atari games with state-dependent safety-labels.
Pretraining the Vision Transformer Using Self-Supervised Methods for Vision Based Deep Reinforcement Learning
Authors: Goulão Manuel , Oliveira Arlindo L.
Published: September 2023

The Vision Transformer architecture has shown to be competitive in the computer vision (CV) space where it has dethroned convolution-based networks in several benchmarks. Nevertheless, convolutional neural networks (CNN) remain the preferential architecture for the representation module in reinforcement learning. In this work, we study pretraining a Vision Transformer using several state-of-the-art self-supervised methods and assess the quality of the learned representations. To show the importance of the temporal dimension in this context we propose an extension of VICReg to better capture temporal relations between observations by adding a temporal order verification task. Our results show that all methods are effective in learning useful representations and avoiding representational collapse for observations from the Atari Learning Environment (ALE) which leads to improvements in data efficiency when we evaluated in reinforcement learning (RL). Moreover, the encoder pretrained with the temporal order verification task shows the best results across all experiments, with richer representations, more focused attention maps and sparser representation vectors throughout the layers of the encoder, which shows the importance of exploring such similarity dimension. With this work, we hope to provide some insights into the representations learned by ViT during a self-supervised pretraining with observations from RL environments and to understand which properties arise in the representations that lead to the best-performing agents.
On the Notion of Envy Among Groups of Agents in House Allocation Problems
Authors: Gross-Humbert Nathanaël , Benabbou Nawal , Beynier Aurélie , Maudet Nicolas
Published: September 2023

Envy-freeness is one of the prominent fairness notions in multiagent resource allocation but it has been mainly studied from an individual point of view. When the agents are partitioned into groups, fairness between groups is desirable. Several notions of group envy-freeness have been proposed over the last few years in the domain of fair division. In this paper we show that when groups may have different sizes and each agent gets at most one item, existing group envy-freeness notions fail to satisfy some desirable axioms. This motivates us to propose an original notion of degree of envy-freeness among groups, based on the counterfactual comparison of subgroups of the same size. While this notion is computationally demanding, we show that it can be efficiently approximated thanks to an adapted sampling method, showing that our approach is of practical relevance.
Is Performance Fairness Achievable in Presence of Attackers Under Federated Learning?
Authors: Gupta Ashish , Markowsky George , Das Sajal K.
Published: September 2023

In the last few years, Federated Learning (FL) has received extensive attention from the research community because of its capability for privacy-preserving, collaborative learning from heterogeneous data sources. Most FL studies focus on either average performance improvement or the robustness to attacks, while some attempt to solve both jointly. However, the performance disparities across clients in the presence of attackers have largely been unexplored. In this work, we propose a novel Fair Federated Learning scheme with Attacker Detection capability (abbreviated as FFL+AD) to minimize performance discrepancies across benign participants. FFL+AD enables the server to identify attackers and learn their malign intent (e.g., targeted label) by investigating suspected models via top performers. This two-step detection method helps reduce false positives. Later, we introduce fairness by regularizing the benign clients’ local objectives with a variable boosting parameter that gives more emphasis on low performers in optimization. Under standard assumptions, FFL+AD exhibits a convergence rate similar to FedAvg. Experimental results show that our scheme builds a more fair and more robust model, under label-flipping and backdoor attackers, compared to prior schemes. FFL+AD achieves competitive accuracy even when 40% of the clients are attackers.
Reasoning Guided by a Manual: Context-Aware Image Captioning with Novel Objects
Authors: Hua Peiyao , Sun Haifeng , Hao Jiachang , Liu Cong , Wang Jingyu , Qi Qi , Liao Jianxin
Published: September 2023

Novel object captioning task aims at describing objects that are absent from training data. Due to the scarcity of novel objects, it’s challenging to find a way to utilize external data to improve model’s reasoning ability. While previously designed methods all follow a deep learning approach, we boost novel object captioning by incorporating reasoning with traditional deep learning framework. We design a manual from dictionaries that provides our model with sufficient and accurate external information on novel objects. We propose Manual-guided Context-aware Novel Object Captioning model (MC-NOC) that utilizes image and caption context to generate novel object captions. It contains a Manual-Guided Novel Object Reasoning module to reason about novel objects based on other objects of the given image and a Caption Reconstruction module to incorporate novel objects into generated captions according to caption context. We validate MC-NOC with state-of-the-art performance on the challenging Held-out COCO and Nocaps dataset, leading their leaderboard. In particular, we improved the CIDER metric by 6.4 points on the held-out coco dataset. Comprehensive experiments demonstrate our model’s reasoning capability and the quality of generated captions.
Diversified Prior Knowledge Enhanced General Language Model for Biomedical Information Retrieval
Authors: Huang Yizheng , Huang Jimmy X.
Published: September 2023

General language models have shown success in various information retrieval (IR) tasks, but their effectiveness is limited in the biomedical domain due to the specialized and complex nature of biomedical data. However, training domain-specific models is challenging and costly due to the limited availability of annotated data. To address these issues, we propose the Diversified Prior Knowledge Enhanced General Language Model (DPK-GLM) framework, which integrates domain knowledge with general language models for improved performance in biomedical IR. Our two-stage retrieval framework comprises a Knowledge-based Query Expansion method for enriching biomedical knowledge, an Aspect-based Filter for identifying highly-relevant documents, and a Diversity-based Score Reweighting method for re-ranking retrieved documents. Experimental results on public biomedical IR datasets show significant improvement, demonstrating the effectiveness of the proposed methods.
Automatic Parallel Portfolio Selection
Authors: Kashgarani Haniye , Kotthoff Lars
Published: September 2023

Algorithms to solve hard combinatorial problems often exhibit complementary performance, i.e. where one algorithm fails, another shines. Algorithm portfolios and algorithm selection take advantage of this by running all algorithms in parallel or choosing the best one to run on a problem instance. In this paper, we show that neither of these approaches gives the best possible performance and propose the happy medium of running a subset of all algorithms in parallel. We propose a method to choose this subset automatically for each problem instance, and demonstrate empirical improvements of up to 19% in terms of runtime, 81% in terms of misclassification penalty, and 26% in terms of penalized averaged runtime on scenarios from the ASlib benchmark library. Unlike all other algorithm selection and scheduling approaches in the literature, our performance measures are based on the actual performance for algorithms running in parallel rather than assuming overhead-free parallelization based on sequential performance. Our approach is easy to apply in practice and does not require to solve hard problems to obtain a schedule, unlike other techniques in the literature, while still delivering superior performance.
Approximate Data Deletion in Generative Models
Authors: Kong Zhifeng , Alfeld Scott
Published: September 2023

Users have the right to have their data deleted by third-party learned systems, as codified by recent legislation such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). Such data deletion can be achieved by full re-training, but this incurs a high computational cost for modern machine learning methods. To avoid this cost, many approximate deletion methods have been developed for supervised learning. Unsupervised learning, in contrast, remains largely an open problem when it comes to efficient approximate data deletion. In this paper, we introduce (1) an efficient method for approximate deletion in generative models, and (2) statistical tests for estimating whether training points have been deleted. We provide theoretical guarantees under various learner assumptions. We then empirically demonstrate our methods across a variety of generative methods.
Spectral Normalized-Cut Graph Partitioning with Fairness Constraints
Authors: Li Jia , Wang Yanhao , Merchant Arpit
Published: September 2023

Normalized-cut graph partitioning aims to divide the set of nodes in a graph into k disjoint clusters to minimize the fraction of the total edges between any cluster and all other clusters. In this paper, we consider a fair variant of the partitioning problem wherein nodes are characterized by a categorical sensitive attribute (e.g., gender or race) indicating membership to different demographic groups. Our goal is to ensure that each group is approximately proportionally represented in each cluster while minimizing the normalized cut value. To resolve this problem, we propose a two-phase spectral algorithm called FNM. In the first phase, we add an augmented Lagrangian term based on our fairness criteria to the objective function for obtaining a fairer spectral node embedding. Then, in the second phase, we design a rounding scheme to produce k clusters from the fair embedding that effectively trades off fairness and partition quality. Through comprehensive experiments on nine benchmark datasets, we demonstrate the superior performance of FNM compared with three baseline methods.