Central European University

Qualitative Comparative Analysis (QCA) and other set-theoretic methods distinguish themselves from other approaches to the study of social phenomena by using sets and the search for set relations. In virtually all social science fields, statements about social phenomena can be framed in terms of set relations, and using set-theoretic methods to investigate these statements is therefore highly valuable. This book guides readers through the basic principles of set theory and then on to the applied practices of QCA. It provides a thorough understanding of basic and advanced issues in set-theoretic methods together with tricks of the trade, software handling and exercises. Most arguments are introduced using examples from existing research. The use of QCA is increasing rapidly and the application of set-theory is both fruitful and still widely misunderstood in current empirical comparative social research. This book provides the comprehensive guide to these methods for researchers across the social sciences.

Researchers from across the social sciences have found consistent deviations from the predictions of the canonical model of self-interest in hundreds of experiments from around the world. This research, however, cannot determine whether the uniformity results from universal patterns of human behavior or from the limited cultural variation available among the university students used in virtually all prior experimental work. To address this, we undertook a cross-cultural study of behavior in ultimatum, public goods, and dictator games in a range of small-scale societies exhibiting a wide variety of economic and cultural conditions. We found, first, that the canonical model - based on self-interest - fails in all of the societies studied. Second, our data reveal substantially more behavioral variability across social groups than has been found in previous research. Third, group-level differences in economic organization and the structure of social interactions explain a substantial portion of the behavioral variation across societies: the higher the degree of market integration and the higher the payoffs to cooperation in everyday life, the greater the level of prosociality expressed in experimental games. Fourth, the available individual-level economic and demographic variables do not consistently explain game behavior, either within or across groups. Fifth, in many cases experimental play appears to reflect the common interactional patterns of everyday life.

Aus dem Dt. übers. - "Qualitative Comparative Analysis (QCA) and other set-theoretic methods distinguish themselves from other approaches to the study of social phenomena by using sets and the search for set relations. In virtually all social science fields, statements about social phenomena can be framed in terms of set relations, and using set-theoretic methods to investigate these statements is therefore highly valuable. This book guides readers through the basic principles of set theory and then on to the applied practices of QCA. It provides a thorough understanding of basic and advanced issues in set-theoretic methods together with tricks of the trade, software handling and exercises. Most arguments are introduced using examples from existing research. The use of QCA is increasing rapidly and the application of set-theory is both fruitful and still widely misunderstood in current empirical comparative social research. This book provides an invaluable guide to these methods for researchers across the social sciences"

v4.10.0: LayoutLM-v2, LayoutXLM, BEiT LayoutLM-v2 and LayoutXLM Four new models are released as part of the LatourLM-v2 implementation: <code>LayoutLMv2ForSequenceClassification</code>, <code>LayoutLMv2Model</code>, <code>LayoutLMv2ForTokenClassification</code> and <code>LayoutLMv2ForQuestionAnswering</code>, in PyTorch. The LayoutLMV2 model was proposed in LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document Understanding by Yang Xu, Yiheng Xu, Tengchao Lv, Lei Cui, Furu Wei, Guoxin Wang, Yijuan Lu, Dinei Florencio, Cha Zhang, Wanxiang Che, Min Zhang, Lidong Zhou. LayoutLMV2 improves LayoutLM to obtain state-of-the-art results across several document image understanding benchmarks: Add LayoutLMv2 + LayoutXLM #12604 (@NielsRogge) Compatible checkpoints can be found on the Hub: https://huggingface.co/models?filter=layoutlmv2 BEiT Three new models are released as part of the BEiT implementation: <code>BeitModel</code>, <code>BeitForMaskedImageModeling</code>, and <code>BeitForImageClassification</code>, in PyTorch. The BEiT model was proposed in BEiT: BERT Pre-Training of Image Transformers by Hangbo Bao, Li Dong and Furu Wei. Inspired by BERT, BEiT is the first paper that makes self-supervised pre-training of Vision Transformers (ViTs) outperform supervised pre-training. Rather than pre-training the model to predict the class of an image (as done in the original ViT paper), BEiT models are pre-trained to predict visual tokens from the codebook of OpenAI's DALL-E model given masked patches. Add BEiT #12994 (@NielsRogge) Compatible checkpoints can be found on the Hub: https://huggingface.co/models?filter=beit Speech improvements The Wav2Vec2 and HuBERT models now have a sequence classification head available. Add Wav2Vec2 &amp; Hubert ForSequenceClassification #13153 (@anton-l) DeBERTa in TensorFlow (@kamalkraj) The DeBERTa and DeBERTa-v2 models have been converted from PyTorch to TensorFlow. Deberta tf #12972 (@kamalkraj) Deberta_v2 tf #13120 (@kamalkraj) Flax model additions EncoderDecoder, DistilBERT, and ALBERT, now have support in Flax! FlaxEncoderDecoder allowing Bert2Bert and Bert2GPT2 in Flax #13008 (@ydshieh) FlaxDistilBERT #13324 (@kamalkraj) FlaxAlBERT #13294 (@kamalkraj) TensorFlow examples A new example has been added in TensorFlow: multiple choice! Data collators have become framework agnostic and can now work for both TensorFlow and NumPy on top of PyTorch. Add TF multiple choice example #12865 (@Rocketknight1) TF/Numpy variants for all DataCollator classes #13105 (@Rocketknight1) Auto API refactor The Auto APIs have been disentangled from all the other mode modules of the Transformers library, so you can now safely import the Auto classes without importing all the models (and maybe getting errors if your setup is not compatible with one specific model). The actual model classes are only imported when needed. Disentangle auto modules from other modeling files #13023 (@sgugger) Fix AutoTokenizer when no fast tokenizer is available #13336 (@sgugger) Slight breaking change When loading some kinds of corrupted state dictionaries of models, the <code>PreTrainedModel.from_pretrained</code> method was sometimes silently ignoring weights. This has now become a real error. Fix from_pretrained with corrupted state_dict #12939 (@sgugger) General improvements and bugfixes Improving pipeline tests #12784 (@Narsil) Pin git python to &lt;3.1.19 #12858 (@patrickvonplaten) [tests] fix logging_steps requirements #12860 (@stas00) [Sequence Feature Extraction] Add truncation #12804 (@patrickvonplaten) add <code>classifier_dropout</code> to classification heads #12794 (@PhilipMay) Fix barrier for SM distributed #12853 (@sgugger) Add possibility to ignore imports in test_fecther #12801 (@sgugger) Add accelerate to examples requirements #12888 (@sgugger) Fix documentation of BigBird tokenizer #12889 (@sgugger) Better heuristic for token-classification pipeline. #12611 (@Narsil) Fix push_to_hub for TPUs #12895 (@sgugger) <code>Seq2SeqTrainer</code> set max_length and num_beams only when non None #12899 (@cchen-dialpad) [FLAX] Minor fixes in CLM example #12914 (@stefan-it) Correct validation_split_percentage argument from int (ex:5) to float (0.05) #12897 (@Elysium1436) Fix typo in the example of MobileBertForPreTraining #12919 (@buddhics) Add option to set max_len in run_ner #12929 (@sgugger) Fix QA examples for roberta tokenizer #12928 (@sgugger) Print defaults when using --help for scripts #12930 (@sgugger) Fix StoppingCriteria ABC signature #12918 (@willfrey) Add missing @classmethod decorators #12927 (@willfrey) fix distiller.py #12910 (@chutaklee) Update generation_logits_process.py #12901 (@willfrey) Update generation_logits_process.py #12900 (@willfrey) Update tokenization_auto.py #12896 (@willfrey) Fix docstring typo in tokenization_auto.py #12891 (@willfrey) [Flax] Correctly Add MT5 #12988 (@patrickvonplaten) ONNX v2 raises an Exception when using PyTorch &lt; 1.8.0 #12933 (@mfuntowicz) Moving feature-extraction pipeline to new testing scheme #12843 (@Narsil) Add CpmTokenizerFast #12938 (@JetRunner) fix typo in gradient_checkpointing arg #12855 (@21jun) Log Azure ML metrics only for rank 0 #12766 (@harshithapv) Add substep end callback method #12951 (@wulu473) Add multilingual documentation support #12952 (@JetRunner) Fix division by zero in NotebookProgressPar #12953 (@sgugger) [FLAX] Minor fixes in LM example #12947 (@stefan-it) Prevent <code>Trainer.evaluate()</code> crash when using only tensorboardX #12963 (@aphedges) Fix typo in example of DPRReader #12954 (@tadejsv) Place BigBirdTokenizer in sentencepiece-only objects #12975 (@sgugger) fix typo in example/text-classification README #12974 (@fullyz) Fix template for inputs docstrings #12976 (@sgugger) fix <code>Trainer.train(resume_from_checkpoint=False)</code> is causing an exception #12981 (@PhilipMay) Cast logits from bf16 to fp32 at the end of TF_T5 #12332 (@szutenberg) Update CANINE test #12453 (@NielsRogge) pad_to_multiple_of added to DataCollatorForWholeWordMask #12999 (@Aktsvigun) [Flax] Align jax flax device name #12987 (@patrickvonplaten) [Flax] Correct flax docs #12782 (@patrickvonplaten) T5: Create position related tensors directly on device instead of CPU #12846 (@armancohan) Skip ProphetNet test #12462 (@LysandreJik) Create perplexity.rst #13004 (@sashavor) GPT-Neo ONNX export #12911 (@michaelbenayoun) Update generate method - Fix floor_divide warning #13013 (@nreimers) [Flax] Correct pt to flax conversion if from base to head #13006 (@patrickvonplaten) [Flax T5] Speed up t5 training #13012 (@patrickvonplaten) FX submodule naming fix #13016 (@michaelbenayoun) T5 with past ONNX export #13014 (@michaelbenayoun) Fix ONNX test: Put smaller ALBERT model #13028 (@LysandreJik) Tpu tie weights #13030 (@sgugger) Use min version for huggingface-hub dependency #12961 (@lewtun) tfhub.de -&gt; tfhub.dev #12565 (@abhishekkrthakur) [Flax] Refactor gpt2 &amp; bert example docs #13024 (@patrickvonplaten) Add MBART to models exportable with ONNX #13049 (@LysandreJik) Add to ONNX docs #13048 (@LysandreJik) Fix small typo in M2M100 doc #13061 (@SaulLu) Add try-except for torch_scatter #13040 (@JetRunner) docs: add HuggingArtists to community notebooks #13050 (@AlekseyKorshuk) Fix ModelOutput instantiation form dictionaries #13067 (@sgugger) Roll out the test fetcher on push tests #13055 (@sgugger) Fix fallback of test_fetcher #13071 (@sgugger) Revert to all tests whil we debug what's wrong #13072 (@sgugger) Use original key for label in DataCollatorForTokenClassification #13057 (@ibraheem-moosa) [Doctest] Setup, quicktour and task_summary #13078 (@sgugger) Add VisualBERT demo notebook #12263 (@gchhablani) Install git #13091 (@LysandreJik) Fix classifier dropout in AlbertForMultipleChoice #13087 (@ibraheem-moosa) Doctests job #13088 (@LysandreJik) Fix VisualBert Embeddings #13017 (@gchhablani) Proper import for unittest.mock.patch #13085 (@sgugger) Reactive test fecthers on scheduled test with proper git install #13097 (@sgugger) Change a parameter name in FlaxBartForConditionalGeneration.decode() #13074 (@ydshieh) [Flax/JAX] Run jitted tests at every commit #13090 (@patrickvonplaten) Rely on huggingface_hub for common tools #13100 (@sgugger) [FlaxCLIP] allow passing params to image and text feature methods #13099 (@patil-suraj) Ci last fix #13103 (@sgugger) Improve type checker performance #13094 (@bschnurr) Fix VisualBERT docs #13106 (@gchhablani) Fix CircleCI nightly tests #13113 (@sgugger) Create py.typed #12893 (@willfrey) Fix flax gpt2 hidden states #13109 (@ydshieh) Moving fill-mask pipeline to new testing scheme #12943 (@Narsil) Fix omitted lazy import for xlm-prophetnet #13052 (@minwhoo) Fix classifier dropout in bertForMultipleChoice #13129 (@mandelbrot-walker) Fix frameworks table so it's alphabetical #13118 (@osanseviero) [Feature Processing Sequence] Remove duplicated code #13051 (@patrickvonplaten) Ci continue through smi failure #13140 (@LysandreJik) Fix missing <code>seq_len</code> in <code>electra</code> model when <code>inputs_embeds</code> is used. #13128 (@sararb) Optimizes ByT5 tokenizer #13119 (@Narsil) Add splinter #12955 (@oriram) [AutoFeatureExtractor] Fix loading of local folders if config.json exists #13166 (@patrickvonplaten) Fix generation docstrings regarding input_ids=None #12823 (@jvamvas) Update namespaces inside torch.utils.data to the latest. #13167 (@qqaatw) Fix the loss calculation of ProphetNet #13132 (@StevenTang1998) Fix LUKE tests #13183 (@NielsRogge) Add min and max question length options to TapasTokenizer #12803 (@NielsRogge) SageMaker: Fix sagemaker DDP &amp; metric logs #13181 (@philschmid) correcting group beam search function output score bug #13211 (@sourabh112) Change how "additional_special_tokens" argument in the ".from_pretrained" method of the tokenizer is taken into account #13056 (@SaulLu) remove unwanted control-flow code from DeBERTa-V2 #13145 (@kamalkraj) Fix load_tf_weights alias. #13159 (@qqa

Post-Communist Party Systems examines democratic party competition in four post-communist polities in the mid-1990s: Bulgaria, the Czech Republic, Hungary, and Poland. Legacies of pre-communist rule turn out to play as much a role in accounting for differences as the institutional differences incorporated in the new democratic rules of the game. The book demonstrates various developments within the four countries with regard to different voter appeal of parties, patterns of voter representation, and dispositions to join other parties in legislative or executive alliances. The authors also present interesting avenues of comparison for broader sets of countries.

We summarize the estimates from over 200 recent studies of active labor market programs. We classify the estimates by type of program and participant group, and distinguish between three different post-program time horizons. Using regression models for the estimated program effect (for studies that model the probability of employment) and for the sign and significance of the estimated effect (for all the studies in our sample) we conclude that: (1) average impacts are close to zero in the short run, but become more positive 2–3 years after completion of the program; (2) the time profile of impacts varies by type of program, with larger average gains for programs that emphasize human capital accumulation; (3) there is systematic heterogeneity across participant groups, with larger impacts for females and participants who enter from long term unemployment; (4) active labor market programs are more likely to show positive impacts in a recession.

This paper focuses on the role of international actors in policy/ knowledge transfer processes to suggest a dynamic for the transnationalization of policy results. The paper seeks to redress the tendency towards methodological nationalism in much of the early policy transfer literature by bringing to the fore the role of international organizations and non-state actors in transnational transfer networks. Secondly, attention is drawn to ‘soft’ forms of transfer – such as the spread of norms – as a necessary complement to the hard transfer of policy tools, structures and practices and in which non-state actors play a more prominent role. Thirdly, transnational networks are identified as an important vehicle for the spread of policy and practice not only cross-nationally but in emergent venues of global governance.

Drug combinations, offering increased therapeutic efficacy and reduced toxicity, play an important role in treating multiple complex diseases. Yet, our ability to identify and validate effective combinations is limited by a combinatorial explosion, driven by both the large number of drug pairs as well as dosage combinations. Here we propose a network-based methodology to identify clinically efficacious drug combinations for specific diseases. By quantifying the network-based relationship between drug targets and disease proteins in the human protein-protein interactome, we show the existence of six distinct classes of drug-drug-disease combinations. Relying on approved drug combinations for hypertension and cancer, we find that only one of the six classes correlates with therapeutic effects: if the targets of the drugs both hit disease module, but target separate neighborhoods. This finding allows us to identify and validate antihypertensive combinations, offering a generic, powerful network methodology to identify efficacious combination therapies in drug development.

Considering that, in accordance with the principles proclaimed in the Charter of the United Nations, recognition of the inherent dignity and of the equal and inalienable rights of all members of the human family is the foundation of freedom, justice and peace in the world,

In order to avoid both theoretically eclectic and redundant approaches to constructivism, this article proposes one possible and coherent reconstruction of constructivism understood as a reflexive meta-theory. This reconstruction starts by taking seriously the double sociological and interpretivist turn of the social sciences. Based on `double hermeneutics', constructivism is perhaps best understood by distinguishing its position on the level of observation, the level of action proper, and the relationship between these two levels. On the basis of this distinction, the article argues that constructivism is epistemologically about the social construction of knowledge and ontologically about the construction of social reality. It furthermore asks us to combine a social theory of knowledge with an intersubjective, not an individualist, theory of action. Finally, the analysis of power is central to understanding the reflexive link between the two levels of observation and action. The argument is embedded in a contextualization where constructivism is seen as inspired by `reflexive modernity', as well as more directly by the end of the Cold War.

All too often, energy policy and technology discussions are limited to the domains of engineering and economics. Many energy consumers, and even analysts and policymakers, confront and frame energy and climate risks in a moral vacuum, rarely incorporating broader social justice concerns. Here, to remedy this gap, we investigate how concepts from justice and ethics can inform energy decision-making by reframing five energy problems — nuclear waste, involuntary resettlement, energy pollution, energy poverty and climate change — as pressing justice concerns. We conclude by proposing an energy justice framework centred on availability, affordability, due process, transparency and accountability, sustainability, equity and responsibility, which highlights the futurity, fairness and equity dimensions of energy production and use. When making decisions about energy, consumers and policymakers typically overlook moral issues, which can have profound societal consequences. This Perspective explores how ideas from justice and ethics can provide a framework to reconsider energy problems and better inform decision-making processes.

Despite the frequent use of numerous quantitative indicators to gauge the professional impact of a scientist, little is known about how scientific impact emerges and evolves in time. Here, we quantify the changes in impact and productivity throughout a career in science, finding that impact, as measured by influential publications, is distributed randomly within a scientist's sequence of publications. This random-impact rule allows us to formulate a stochastic model that uncouples the effects of productivity, individual ability, and luck and unveils the existence of universal patterns governing the emergence of scientific success. The model assigns a unique individual parameter Q to each scientist, which is stable during a career, and it accurately predicts the evolution of a scientist's impact, from the h-index to cumulative citations, and independent recognitions, such as prizes.

Because mutually beneficial cooperation may unravel unless most members of a group contribute, people often gang up on free-riders, punishing them when this is cost-effective in sustaining cooperation. In contrast, current models of the evolution of cooperation assume that punishment is uncoordinated and unconditional. These models have difficulty explaining the evolutionary emergence of punishment because rare unconditional punishers bear substantial costs and hence are eliminated. Moreover, in human behavioral experiments in which punishment is uncoordinated, the sum of costs to punishers and their targets often exceeds the benefits of the increased cooperation that results from the punishment of free-riders. As a result, cooperation sustained by punishment may actually reduce the average payoffs of group members in comparison with groups in which punishment of free-riders is not an option. Here, we present a model of coordinated punishment that is calibrated for ancestral human conditions and captures a further aspect of reality missing from both models and experiments: The total cost of punishing a free-rider declines as the number of punishers increases. We show that punishment can proliferate when rare, and when it does, it enhances group-average payoffs.

The increasing cost of drug development together with a significant drop in the number of new drug approvals raises the need for innovative approaches for target identification and efficacy prediction. Here, we take advantage of our increasing understanding of the network-based origins of diseases to introduce a drug-disease proximity measure that quantifies the interplay between drugs targets and diseases. By correcting for the known biases of the interactome, proximity helps us uncover the therapeutic effect of drugs, as well as to distinguish palliative from effective treatments. Our analysis of 238 drugs used in 78 diseases indicates that the therapeutic effect of drugs is localized in a small network neighborhood of the disease genes and highlights efficacy issues for drugs used in Parkinson and several inflammatory disorders. Finally, network-based proximity allows us to predict novel drug-disease associations that offer unprecedented opportunities for drug repurposing and the detection of adverse effects.

Abstract The post‐ M aastricht period is marked by an integration paradox. While the basic constitutional features of the E uropean Union have remained stable, EU activity has expanded to an unprecedented degree. This form of integration without supranationalism is no exception or temporary deviation from traditional forms of E uropean integration. Rather, it is a distinct phase of E uropean integration, what is called ‘the new intergovernmentalism’ in this article. This approach to post‐ M aastricht integration challenges theories that associate integration with transfers of competences from national capitals to supranational institutions and those that reduce integration to traditional socioeconomic or security‐driven interests. This article explains the integration paradox in terms of transformations in E urope's political economy, changes in preference formation and the decline of the ‘permissive consensus’. It presents a set of six hypotheses that develop further the main claims of the new intergovernmentalism and that can be used as a basis for future research.

Migration studies have focused attention on ethnic institutions in global and gateway cities. This ethnic lens distorts migration scholarship, reinforces methodological nationalism, and disregards the role of city scale in shaping migrant pathways of settlement and transnational connection. The scale of cities reflects their positioning within neoliberal processes of local, national, regional, and global rescaling. To encourage further explorations of nonethnic pathways that may be salient in small-scale cities, we examine born-again Christianity as a means of migrant incorporation locally and transnationally in two small-scale cities, one in the United States and the other in Germany.

Public policy has been a prisoner of the word “state.” Yet, the state is reconfigured by globalization. Through “global public–private partnerships” and “transnational executive networks,” new forms of authority are emerging through global and regional policy processes that coexist alongside nation‐state policy processes. Accordingly, this article asks what is “global public policy”? The first part of the article identifies new public spaces where global policies occur. These spaces are multiple in character and variety and will be collectively referred to as the “global agora .” The second section adapts the conventional policy cycle heuristic by conceptually stretching it to the global and regional levels to reveal the higher degree of pluralization of actors and multiple‐authority structures than is the case at national levels. The third section asks: who is involved in the delivery of global public policy? The focus is on transnational policy communities. The global agora is a public space of policymaking and administration, although it is one where authority is more diffuse, decision making is dispersed and sovereignty muddled. Trapped by methodological nationalism and an intellectual agoraphobia of globalization, public policy scholars have yet to examine fully global policy processes and new managerial modes of transnational public administration.

The availability of massive digital traces of human whereabouts has offered a series of novel insights on the quantitative patterns characterizing human mobility. In particular, numerous recent studies have lead to an unexpected consensus: the considerable variability in the characteristic travelled distance of individuals coexists with a high degree of predictability of their future locations. Here we shed light on this surprising coexistence by systematically investigating the impact of recurrent mobility on the characteristic distance travelled by individuals. Using both mobile phone and GPS data, we discover the existence of two distinct classes of individuals: returners and explorers. As existing models of human mobility cannot explain the existence of these two classes, we develop more realistic models able to capture the empirical findings. Finally, we show that returners and explorers play a distinct quantifiable role in spreading phenomena and that a correlation exists between their mobility patterns and social interactions.

I make three related proposals concerning the development of receptive communication in human infants. First, I propose that the presence of communicative intentions can be recognized in others' behaviour before the content of these intentions is accessed or inferred. Second, I claim that such recognition can be achieved by decoding specialized ostensive signals. Third, I argue on empirical bases that, by decoding ostensive signals, human infants are capable of recognizing communicative intentions addressed to them. Thus, learning about actual modes of communication benefits from, and is guided by, infants' preparedness to detect infant‐directed ostensive communication.

Despite exceptional experimental efforts to map out the human interactome, the continued data incompleteness limits our ability to understand the molecular roots of human disease. Computational tools offer a promising alternative, helping identify biologically significant, yet unmapped protein-protein interactions (PPIs). While link prediction methods connect proteins on the basis of biological or network-based similarity, interacting proteins are not necessarily similar and similar proteins do not necessarily interact. Here, we offer structural and evolutionary evidence that proteins interact not if they are similar to each other, but if one of them is similar to the other's partners. This approach, that mathematically relies on network paths of length three (L3), significantly outperforms all existing link prediction methods. Given its high accuracy, we show that L3 can offer mechanistic insights into disease mechanisms and can complement future experimental efforts to complete the human interactome.