The number of scientific publications is growing exponentially. Research articles cite other work for various reasons and, therefore, have been studied extensively to associate documents. It is argued that not all references carry the same level of importance. It is essential to understand the reason for citation, called citation intent or function. Text information can contribute well if new natural language processing techniques are applied to capture the context of text data. In this paper, we have used contextualized (...) class='Hi'>word embedding to find the numerical representation of text features. We further investigated the performance of various machine-learning techniques on the numerical representation of text. The performance of each of the classifiers was evaluated on two state-of-the-art datasets containing the text features. In the case of the unbalanced dataset, we observed that the linear Support Vector Machine achieved 86% accuracy for the “background” class, where the training was extensive. For the rest of the classes, including “motivation,” “extension,” and “future,” the machine was trained on less than 100 records; therefore, the accuracy was only 57 to 64%. In the case of a balanced dataset, each of the classes has the same accuracy as trained on the same size of training data. Overall, SVM performed best on both of the datasets, followed by the stochastic gradient descent classifier; therefore, SVM can produce good results as text classification on top of contextual word embedding. (shrink)

Large language models (LLMs) have been proposed as candidate models of human semantics, and as such, they must be able to account for conceptual combination. This work explores the ability of two LLMs, namely, BERT-base and Llama-2-13b, to reveal the implicit meaning of existing and novel compound words. According to psycholinguistic theories, understanding the meaning of a compound (e.g., “snowman”) involves its automatic decomposition into constituent meanings (“snow,” “man”), which are then connected by an implicit semantic relation selected from a (...) set of possible competitors (FOR, MADE OF, BY, …) to obtain a plausible interpretation (“man MADE OF snow”). Here, we leverage the flexibility of LLMs to obtain contextualized representations for both target compounds (e.g., “snowman”) and their implicit interpretations (e.g., “man MADE OF snow”). We demonstrate that replacing a compound with a paraphrased version leads to changes to the embeddings that are inversely proportional to the paraphrase's plausibility, estimated by human raters. While this relation holds for both existing and novel compounds, results obtained for novel compounds are substantially weaker, and older distributional models outperform LLMs. Nonetheless, the present results show that LLMs can offer a valid approximation of the internal structure of compound words posited by cognitive theories, thus representing a promising tool to model word senses that are at once implicit and possible. (shrink)

Regular polysemes are sets of ambiguous words that all share the same relationship between their meanings, such as CHICKEN and LOBSTER both referring to an animal or its meat. To probe how a context embedding model, here exemplified by BERT, represents regular polysemy, we analyzed whether its embeddings support answering sense analogy questions similar to “is the mapping be- tween CHICKEN (as an animal) and CHICKEN (as a meat) the same as that which maps between LOBSTER (as an animal) (...) to LOBSTER (as a meat)?” We found that (1) the model was sensitive to the shared structure within a regularity type; (2) the shared structure varies across regularity types, potentially reflective of a “regularity continuum;” (3) some high-order latent structure may be shared across regularity types, suggestive of a similar la- tent structure across types; and (4) there is equivocal ev- idence that the aforementioned effects are explained by meaning overlap. (shrink)

In this study, we use temporally aligned word embeddings and a large diachronic corpus of English to quantify language change in a data-driven, scalable way, which is grounded in language use. We show a unique and reliable relation between measures of language change and age of acquisition (AoA) while controlling for frequency, contextual diversity, concreteness, length, dominant part of speech, orthographic neighborhood density, and diachronic frequency variation. We analyze measures of language change tackling both the change in lexical (...) representations and the change in the relation between lexical representations and the words with the most similar usage patterns, showing that they capture different aspects of language change. Our results show a unique relation between language change and AoA, which is stronger when considering neighborhood-level measures of language change: Words with more coherent diachronic usage patterns tend to be acquired earlier. The results support theories positing a link between ontogenetic and ethnogenetic processes in language. (shrink)

We examined whether variations in contextual diversity, spacing, and retrieval practice influenced how well adults learned new words from reading experience. Eye movements were recorded as adults read novel words embedded in sentences. In the learning phase, unfamiliar words were presented either in the same sentence repeated four times (same context) or in four different sentences (diverse context). Spacing was manipulated by presenting the sentences under distributed or non‐distributed practice. After learning, half of the participants were asked to retrieve the (...) new words, and half had an extra exposure to the new words. Although words experienced in diverse contexts were acquired more slowly during learning, they enjoyed a greater benefit of learning at immediate posttest. Distributed practice also slowed learning, but no benefit was observed at posttest. Although participants who had an extra exposure showed the greatest learning benefit overall, learning also benefited from retrieval opportunity, when words were experienced in diverse contexts. These findings demonstrate that variation in the content and structure of the learning environment impacts on word learning via reading. (shrink)

Regular polysemes are sets of ambiguous words that all share the same relationship between their meanings, such as CHICKEN and LOBSTER both referring to an animal or its meat. To probe how a distributional semantic model, here exemplified by bidirectional encoder representations from transformers (BERT), represents regular polysemy, we analyzed whether its embeddings support answering sense analogy questions similar to “is the mapping between CHICKEN (as an animal) and CHICKEN (as a meat) similar to that which maps between LOBSTER (...) (as an animal) to LOBSTER (as a meat)?” We did so using the LRcos model, which combines a logistic regression classifier of different categories (e.g., animal vs. meat) with a measure of cosine similarity. We found that (a) the model was sensitive to the shared structure within a given regular relationship; (b) the shared structure varies across different regular relationships (e.g., animal/meat vs. location/organization), potentially reflective of a “regularity continuum;” (c) some high-order latent structure is shared across different regular relationships, suggestive of a similar latent structure across different types of relationships; and (d) there is a lack of evidence for the aforementioned effects being explained by meaning overlap. Lastly, we found that both components of the LRcos model made important contributions to accurate responding and that a variation of this method could yield an accuracy boost of 10% in answering sense analogy questions. These findings enrich previous theoretical work on regular polysemy with a computationally explicit theory and methods, and provide evidence for an important organizational principle for the mental lexicon and the broader conceptual knowledge system. (shrink)

With two eye movements tracking experiments, present study sought to establish whether predictability of target words facilitate characters processing in Chinese reading. Target Words embedded in sentences in both experiments were composed by 2 Chinese characters. Predictability of target words were manipulated in both experiments, beyond that, frequency of targets' first characters were manipulated in Experiment 1, frequency of targets' second characters were manipulated in Experiment 2. Pervasive predictability effects were observed on almost all of eye movement measures in both (...) experiments. It also yield reliable characters frequency effect in Experiment 1 & 2, on some measures. None reliable interaction effects of predictability and first character frequency were observed in Experiment 1, but predictability and second character frequency interactively impacted on some measures of eye movement. Theoretical implications of the data are discussed. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:A Wittgensteinian Approach to Discerning the Meaning of Works of Art in the Practice of Critical and Contextual Studies in Secondary Art EducationLeslie Cunliffe (bio)In order to get clear about aesthetic words you have to describe ways of living.Wittgenstein, Lectures and Conversations on Aesthetics, Psychology and Religious Belief1Language is a labyrinth of paths. You approach from one side and know your way about; you approach the same place from (...) another side and no longer know your way about.Wittgenstein, Philosophical Investigations2IntroductionThis article explores a Wittgensteinian approach for dealing with the meaning of works of art in the practice of critical and contextual studies in art education. The article is aimed at developing a methodology for eleven to nineteen year olds, known in the UK as the secondary phase of education, but the approach could be generalized to other educational phases.Henry Finch3 interprets four references to meaning found in Ludwig Wittgenstein's philosophy of language as a quadrant that combines the horizontal axis of meaning as physiognomies (the experiential and visual) and meaning as constructions (concepts, uses, science, and mathematics), with a vertical axis of meaning as imperatives (rule following, obligations, and law) and meaning as custom (ceremonies, myths, and ritual).4 The quadrant represents Finch's understanding of Wittgenstein's views about how language serves a different but complementary role in the way human beings engage [End Page 65] with meaning in the world and their place in it.5 Such meanings are embedded in social practices, including first-person responses to a physiognomy, although these start off as biologically primed reactions.Michael Luntley argues that Wittgenstein's philosophy of language and the related remarks on perception should be understood as setting conditions for the possibilities of judgment in "seeing the world aright, in taking the right attitude to the world"6 rather than simply mapping the possibilities of meaning, as the former underscores the role of will7 in the way meaning is actively witnessed and ethically processed by an agent. Having the right view is still only a view, but for Wittgenstein this amounted to an immense ethical and philosophical project to see things accurately and in correct relationship to each other. Such perspectival stances result from an agent's capacity to selectively engage with meaning, with a more unitary understanding resulting from criss-crossing the same territory from different points of view. Wittgenstein's four references to meaning can be thought of as forming four different points on a compass that direct the "self-as-will engaged with that which is independent of will "8 in a quest to see things aright. By extension, such an approach could be used in art education to enable students to develop the dispositions to see works of art aright.Marcia Eaton describes the tension between epistemic and interpretative approaches to the meaning of works of art in this way: "In which direction should one go? In other words, how can judgments which seem so personal (relative, subjective, etc.) also play a role in interpersonal (absolute, objective, etc.) language games?"9 Michael Podro gives a similar description of the apparent tension between a context-bound analysis of works of art and their irreducible and autonomous qualities as like "constantly treading a tightrope."10 Ralph Smith highlights the difference "between having knowledge about art and personally experiencing its presence and power."11Ben Tilghman12 advocates a Wittgensteinian way of going beyond these twofold approaches for understanding and interpreting art by focusing on the role that ponderable and imponderable evidence play in achieving the right stance when attempting to condense the meaning of works of art. Following Wittgenstein, Tilghman argues that a judgment based on imponderable evidence can often be supported by ponderable evidence, a process that is always linked to the relative experience, knowledge, and wisdom of the person making the judgment. Wittgenstein's four references to meaning could be thought of as points on a compass for directing the will in fittingness when endeavoring to understand the role and relationship of ponderable and imponderable evidence in any attempt to see works of art aright. But before these ideas can be... (shrink)

Job seekers find themselves increasingly duped and misled by fraudulent job advertisements, posing a threat to their privacy, security and well-being. There is a clear need for solutions that can protect innocent job seekers. Existing approaches to detecting fraudulent jobs do not scale well, function like a black-box, and lack interpretability, which is essential to guide applicants’ decision-making. Moreover, commonly used lexical features may be insufficient as the representation does not capture contextual semantics of the underlying document. Hence, this paper (...) explores to what extent different categorizations of fraudulent jobs can be classified. In addition, this paper seeks to find what type of features are most relevant in classifying the type of fraudulent job. In this paper, we develop and validate a machine learning system for identifying identity theft, corporate identity theft and multi-level marketing amongst fraudulent job advertisements. We utilized four classes of features: empirical rule set-based features, bag-of-word models, most recent state-of-the-art word embeddings and transformer models for various machine learning classifiers. The machine learning models were validated by evaluating them on a publicly available job description dataset. Our results indicate that the word embeddings and transformer-based features consistently outperformed the handcrafted rule-set based features class. Ultimately, a Gradient Boosting classifier with a combination of empirical rule-set based features, parts-of-speech tags and bag-of-words vectors achieved the best performance with an F1-score of 0.88. (shrink)

When people make decisions, they act in a way that is either automatic (“rote”), or more thoughtful (“reflective”). But do people notice when others are behaving in a rote way, and do they care? We examine the detection of rote behavior and its consequences in U.S. adults, focusing specifically on pedagogy and learning. We establish repetitiveness as a cue for rote behavior (Experiment 1), and find that rote people are seen as worse teachers (Experiment 2). We also find that the (...) more a person's feedback seems similar across groups (indicating greater rote-ness), the more negatively their teaching is evaluated (Experiment 3). A word-embedding analysis of an open-response task shows people naturally cluster rote and reflective teachers into different semantic categories (Experiment 4). We also show that repetitiveness can be decoupled from perceptions of rote-ness given contextual explanation (Experiment 5). Finally, we establish two additional cues to rote behavior that can be tied to quality of teaching (Experiment 6). These results empirically show that people detect and care about scripted behaviors in pedagogy, and suggest an important extension to formal frameworks of social reasoning. (shrink)

If a trademark becomes a generic term, it may be cancelled under trademark law, a process known as genericide. Typically, in genericide cases, consumer surveys are brought into evidence to establish a mark’s semantic status as generic or distinctive. Some drawbacks of surveys are cost, delay, small sample size, lack of reproducibility, and observer bias. Today, however, much discourse involving marks is online. As a potential complement to consumer surveys, therefore, we explore an artificial intelligence approach based chiefly on (...) class='Hi'>word embeddings: mathematical models of meaning based on distributional semantics that can be trained on texts selected for jurisdictional and temporal relevance. After identifying two main factors in mark genericness, we first offer a simple screening metric based on the ngram frequency of uncapitalized variants of a mark. We then add two word embedding metrics: one addressing contextual similarity of uncapitalized variants, and one comparing the neighborhood density of marks and known generic terms in a category. For clarity and validation, we illustrate our metrics with examples of genericized, somewhat generic, and distinctive marks such as, respectively, DUMPSTER, DOBRO, and ROLEX. (shrink)

Applying machine learning algorithms to automatically infer relationships between concepts from large-scale collections of documents presents a unique opportunity to investigate at scale how human semantic knowledge is organized, how people use it to make fundamental judgments (“How similar are cats and bears?”), and how these judgments depend on the features that describe concepts (e.g., size, furriness). However, efforts to date have exhibited a substantial discrepancy between algorithm predictions and human empirical judgments. Here, we introduce a novel approach to generating (...) embeddings for this purpose motivated by the idea that semantic context plays a critical role in human judgment. We leverage this idea by constraining the topic or domain from which documents used for generating embeddings are drawn (e.g., referring to the natural world vs. transportation apparatus). Specifically, we trained state-of-the-art machine learning algorithms using contextually-constrained text corpora (domain-specific subsets of Wikipedia articles, 50+ million words each) and showed that this procedure greatly improved predictions of empirical similarity judgments and feature ratings of contextually relevant concepts. Furthermore, we describe a novel, computationally tractable method for improving predictions of contextually-unconstrained embedding models based on dimensionality reduction of their internal representation to a small number of contextually relevant semantic features. By improving the correspondence between predictions derived automatically by machine learning methods using vast amounts of data and more limited, but direct empirical measurements of human judgments, our approach may help leverage the availability of online corpora to better understand the structure of human semantic representations and how people make judgments based on those. (shrink)

This paper explores the metaphysical concepts of divine “love” (ʿeshq), “attraction” (jadhbe), and “selflessness” (bīkhodī) in the seminal Iranian Shīʿī Muslim thinker Mullā Muḥsin Fayḍ Kāshānī’s poetry. This research emerges from the gap in existing literature, which mainly explores Fayḍ Kāshānī’s philosophical, theological, or ḥadīth works, while the scrutiny of his poetry largely stays within its literary attributes, overlooking the philosophical and mystical themes embedded within. The paper’s thesis posits that according to Fayḍ Kāshānī, the spiritual journey commences with reason, (...) progressing to constant divine contemplation, a combination that nurtures muḥabbat—an initial stage of divine love—which, when discovered, evokes a more intense love: “divine attraction” in the seeker’s heart, leading to selflessness and divine unity. This paper employs the hermeneutic method and analytical examination to scrutinize Fayḍ Kāshānī’s poetry within the context of his treatises. It follows an “intracultural” interpretation to explore Fayḍ Kāshānī’s thought within Persian intellectual tradition and uses an “intercultural” interpretation to contextualize the findings within Islamic, Christian, and ancient Greek metaphysics. The methodology includes a “horizontal interpretation” of Quranic and ḥadīth references in Fayḍ Kāshānī’s works and a “vertical interpretation” of unveiling deeper meanings of Fayḍ Kāshānī’s thoughts within the broader mystical traditions. (shrink)

From Curriculum Vitae parsing to web search and recommendation systems, Word2Vec and other word embedding techniques have an increasing presence in everyday interactions in human society. Biases, such as gender bias, have been thoroughly researched and evidenced to be present in word embeddings. Most of the research focuses on discovering and mitigating gender bias within the frames of the vector space itself. Nevertheless, whose bias is reflected in word embeddings has not yet been investigated. Besides (...) discovering and mitigating gender bias, it is also important to examine whether a feminine or a masculine-centric view is represented in the biases of word embeddings. This way, we will not only gain more insight into the origins of the before mentioned biases, but also present a novel approach to investigating biases in Natural Language Processing systems. Based on previous research in the social sciences and gender studies, we hypothesize that masculine-centric, otherwise known as androcentric, biases are dominant in word embeddings. To test this hypothesis we used the largest English word association test data set publicly available. We compare the distance of the responses of male and female participants to cue words in a word embedding vector space. We found that the word embedding is biased towards a masculine-centric viewpoint, predominantly reflecting the worldviews of the male participants in the word association test data set. Therefore, by conducting this research, we aimed to unravel another layer of bias to be considered when examining fairness in algorithms. (shrink)

The use of ensemble learning, deep learning, and effective document representation methods is currently some of the most common trends to improve the overall accuracy of a text classification/categorization system. Ensemble learning is an approach to raise the overall accuracy of a classification system by utilizing multiple classifiers. Deep learning-based methods provide better results in many applications when compared with the other conventional machine learning algorithms. Word embeddings enable representation of words learned from a corpus as vectors that (...) provide a mapping of words with similar meaning to have similar representation. In this study, we use different document representations with the benefit of word embeddings and an ensemble of base classifiers for text classification. The ensemble of base classifiers includes traditional machine learning algorithms such as naïve Bayes, support vector machine, and random forest and a deep learning-based conventional network classifier. We analysed the classification accuracy of different document representations by employing an ensemble of classifiers on eight different datasets. Experimental results demonstrate that the usage of heterogeneous ensembles together with deep learning methods and word embeddings enhances the classification performance of texts. (shrink)

Automatic synonym extraction plays an important role in many natural language processing systems, such as those involving information retrieval and question answering. Recently, research has focused on extracting semantic relations from word embeddings since they capture relatedness and similarity between words. However, using word embeddings alone poses problems for synonym extraction because it cannot determine whether the relation between words is synonymy or some other semantic relation. In this paper, we present a novel solution for this (...) problem by proposing the SynoExtractor pipeline, which can be used to filter similar word embeddings to retain synonyms based on specified linguistic rules. Our experiments were conducted using KSUCCA and Gigaword embeddings and trained with CBOW and SG models. We evaluated automatically extracted synonyms by comparing them with Alma’any Arabic synonym thesauri. We also arranged for a manual evaluation by two Arabic linguists. The results of experiments we conducted show that using the SynoExtractor pipeline enhances the precision of synonym extraction compared to using the cosine similarity measure alone. SynoExtractor obtained a 0.605 mean average precision for the King Saud University Corpus of Classical Arabic with 21% improvement over the baseline and a 0.748 MAP for the Gigaword corpus with 25% improvement. SynoExtractor outperformed the Sketch Engine thesaurus for synonym extraction by 32% in terms of MAP. Our work shows promising results for synonym extraction suggesting that our method can also be used with other languages. (shrink)

Deep Learning has been widely used for tackling challenging natural language processing tasks over the recent years. Similarly, the application of Deep Neural Networks in legal analytics has increased significantly. In this survey, we study the early adaptation of Deep Learning in legal analytics focusing on three main fields; text classification, information extraction, and information retrieval. We focus on the semantic feature representations, a key instrument for the successful application of deep learning in natural language processing. Additionally, we share pre-trained (...) legal word embeddings using the word2vec model over large corpora, comprised legislations from UK, EU, Canada, Australia, USA, and Japan among others. (shrink)

Public companies in the US stock market must annually report their activities and financial performances to the SEC by filing the so-called 10-K form. Recent studies have demonstrated that changes in the textual content of the corporate annual filing can convey strong signals of companies’ future returns. In this study, we combine natural language processing techniques and network science to introduce a novel 10-K-based network, named Lazy Network, that leverages year-on-year changes in companies’ 10-Ks detected using a neural network embedding (...) model. The Lazy Network aims to capture textual changes derived from financial or economic changes on the equity market. Leveraging the Lazy Network, we present a novel investment strategy that attempts to select the least disrupted and stable companies by capturing the peripheries of the Lazy Network. We show that this strategy earns statistically significant risk-adjusted excess returns. Specifically, the proposed portfolios yield up to 95 basis points in monthly five-factor alphas, outperforming similar strategies in the literature. (shrink)

In informal argument, an essential step is to ask what will “resonate” with a particular audience and hence persuade. Marketers, for example, may recommend a certain colour for a new soda can becau...

Distributional models of semantics learn word meanings from contextual co‐occurrence patterns across a large sample of natural language. Early models, such as LSA and HAL (Landauer & Dumais, 1997; Lund & Burgess, 1996), counted co‐occurrence events; later models, such as BEAGLE (Jones & Mewhort, 2007), replaced counting co‐occurrences with vector accumulation. All of these models learned from positive information only: Words that occur together within a context become related to each other. A recent class of distributional models, referred to (...) as neural embedding models, are based on a prediction process embedded in the functioning of a neural network: Such models predict words that should surround a target word in a given context (e.g., word2vec; Mikolov, Sutskever, Chen, Corrado, & Dean, 2013). An error signal derived from the prediction is used to update each word's representation via backpropagation. However, another key difference in predictive models is their use of negative information in addition to positive information to develop a semantic representation. The models use negative examples to predict words that should not surround a word in a given context. As before, an error signal derived from the prediction prompts an update of the word's representation, a procedure referred to as negative sampling. Standard uses of word2vec recommend a greater or equal ratio of negative to positive sampling. The use of negative information in developing a representation of semantic information is often thought to be intimately associated with word2vec's prediction process. We assess the role of negative information in developing a semantic representation and show that its power does not reflect the use of a prediction mechanism. Finally, we show how negative information can be efficiently integrated into classic count‐based semantic models using parameter‐free analytical transformations. (shrink)

I cast doubt on two proposals for doing without mental phrase markers (MPMs). The first is due to Roger Schank and his colleagues at Yale, who constructed comprehension models that relied almost exclusively on semantic and pragmatic resources. I rehearse the striking and pervasive failures of such models and suggest that similar problems will likely plague newer incarnations in the connectionist tradition. The second proposal for doing without MPMs is Devitt’s “brute-causal” conception of language processing, which sees comprehension as a (...) reflex like, associative mapping directly from words and sentences to concepts and thoughts. I argue on empirical grounds that language comprehension, even at the earliest stages, is neither reflex-like nor associative. Setting that aside, I examine Devitt’s distinction between responding to a property and representing something as having it, and show that the operations of the HSPM cannot be mere “responses” in the relevant sense. Parsing requires keeping track of prior context, and the clues that are relevant for a successful parse may be arbitrarily far back and in discontinuous regions of the stimulus stream. To explain the HSPM’s sensitivity to contextually relevant factors, and the resulting flexibility of its decision-making and behavior, we must posit inference-like transitions between MPMs. -/- Keywords Roger Schank • Semantic resources • Pragmatic resources • Passive sentences • Passive questions • Embedded passives • Reflex • Associationism • Connectionism • Brute-causal processing • The Language of Thought Hypothesis (LOTH) • Mentalese • Representing vs. responding • Responding vs. responding-as • Filler-gap processing • Sphex • Flexible behavior • Thematic roles • Incremental processing • Frames • Functional-role semantics • Systematicity • “Mostly-semantic” models • Integrated processing models • Linear structure • Hierarchical structure • Binding ambiguities • Syntactic binding • Positional Template Filling (PTF) • c-command • Precedence vs. dominance relations • Embedded/embodied cognitive science • Fodor Bever and Garrett (FBG) • David Hume • Aristotle. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:A Unique Response to Death:Day of the Dead Fiestas and Communal Articulations of ResistanceDenise Meda-LambruIntroductionPhilosophers such as Octavio Paz and Emilio Uranga theorize death grounded in Mexican circumstances to show an intimate relational dynamic with life. In their view, death is embedded in the everydayness of the living. Carlos A. Sánchez, in "Death and the Colonial Difference," explains that the Mexican idea of death reveals much about the life (...) and the situatedness of those who subscribe to the relational dynamic between life and death. Death is linked to the living, especially for those who are situated in inferiorized positions. In the accounts promoted by Paz and by Uranga, the historical and social conditions of lived experience provide the context for how death is conceived, and, subsequently, treated. They advance Mexican conceptions of death and provide interesting perspectives into how some colonized peoples are resisting narrow narratives of death. This is to say that their approaches do not grant the dominant assumption that death is merely a biological event or a life event ceasing the life of the individual. In this essay, I examine their critiques of dominant assumptions of death to elaborate on conceptions of death contextualized within historical and social entanglements, namely, a Mexican analysis of death. In particular, I utilize Paz's work on Day of the Dead fiestas to study communal practices and theorize the ritual dimensions of the life and death relationship. Through an examination of a Mexican approach to death, I contend that rituals of death help locate the non-dominant social logics that engender resistant activity and cultivate a distinct interconnected communal relation.To develop this position, I clarify the historical and social distinctions between Mexican and Anglo-American approaches to death and analyze literature promoting a Mexican view of death. Ultimately, I share a similar view [End Page 31] with Paz, Uranga, and Sánchez who charge that there is a unique Mexican idea of death. However, to be clear, my interest in their work does not assume they represent the Mexican view of death (Brandes, Skulls to the Living). Rather, I am interested in exploring how their discussions of death, from a particular socio-historical situation, reveal ways in which colonized peoples refuse dichotomous narratives of death. Sánchez's work, in particular, provides valuable insights into the Mexican relation with death, particularly the role of coloniality/modernity with temporality. Lastly, as I return to Paz's own discussion of death, I refer to the sensibilities and practices relevant to the resistant dimensions of a Mexican relationship with death. An analysis of Paz's focus on fiestas offers a focus distinct from Sánchez in that it pays significant attention to the ritual dimensions of death and helps illustrate the resistant responses to hegemonic social norms. Thus, paying attention to communal practices, this essay emphasizes the relationship between death rituals and deviant activity to dominant modes of being.What Is Death? Examining the DistinctionsScholars have noted a distinction between the logics involved in European and Anglo-American approaches to death and those of Mexican people. Emilio Uranga asserts that "[f]or the North American (el norteamericano), death is a reality that must be hidden, a phenomenon that is silenced and masked as much as possible so that it will not disturb, with its impertinence, the flow of a life that unfolds in radical dedication to [self]-realization and work" (qtd. in Sánchez 180). Paz shares a similar view of this concealment. He writes that "the word death is not pronounced in New York, in Paris, in London, because it burns the lips" ("Day of the Dead" 57). Paz describes death for the Euro-Anglo as one that is treated as a stinging topic to be avoided. In both Uranga's view and Paz's view, the Euro-Anglo phenomenon of death is not socially discussed or regarded as part of the daily lived realities of the subject. If we take their accounts as at least generally accurate, then for Anglos, death is something that is to be treated as separate from life.1In distinction, however, the Mexican attitude toward death is described as... (shrink)

Residential segregation according to race remains fairly entrenched in parts of the United States despite the fact that public attitudes toward racial integration have become dramatically more positive. This incongruity is often explained in terms of the irrationality of agents, whereby the agents’ support of integration is undermined by systematic/unconscious racism. The author argues that such accounts present an implausible model of practical rationality and places too great a justificatory burden on the critic/observer perspective. As an alternative, he suggests the (...) problem is a conflict between modes of practical rationality, specifically, between reasons developed from an embedded context and reasons from a general, abstract perspective. Because many whites live in segregated conditions, they develop contextual reasons for preserving that way of life, even if such reasons fly in the face of their sense of justice. This account is more philosophically sound and gives rise to interesting policy recommendations for overcoming segregation. Key Words: segregation • trust • ideology • practical rationality. (shrink)

Since narratives of legitimation have to adapt to shifting discursive environments, they cannot be regarded as static phenomena. To present a sound understanding of their embedment in a specific context, narratives have to be approached from a variety of perspectives – they necessitate, in other words, a “thick description”. This paper addresses the narrative of antifascism as a central element of public discourse throughout the history of the German Democratic Republic and contextualizes it specifically in East German television culture. In (...) addition to providing an understanding of antifascism as an ideological signifier exclusively for historical phenomena, such as National Socialism or Italian fascism, this paper proposes to conceptualize the narrative of antifascism – as it was officially defined in the GDR/SBZ – as a discursive formation that encompasses various political narratives such as militarism and imperialism, as well as past and present political events. Based on this assumption, the highly successful espionage series Das unsichtbare Visier, which was produced by the DEFA and broadcasted by the East German state television, will be discussed in relation to its exploitation of the narrative of antifascism. By approaching these issues, it is the objective of this paper to examine the practices of the appropriation of the narrative of antifascism in an era that was marked by the development of popular television culture and, moreover, to contribute to the discussion of the dialectic between stability and flexibility that is inherent to narratives. (shrink)

The present work investigates the memory accessibility of linguistically focused elements and the representation of the alternatives for these elements in Working Memory and in delayed recognition memory in the case of the Hungarian pre-verbal focus construction. In two probe recognition experiments we presented preVf and corresponding focusless neutral sentences embedded in five-sentence stories. Stories were followed by the presentation of sentence probes in one of three conditions: the probe was identical to the original sentence in the story, the focused (...) word was replaced by a semantically related word and the target word was replaced by a semantically unrelated but contextually suitable word. In Experiment 1, probes were presented immediately after the stories measuring WM performance, while in Experiment 2, blocks of six stories were presented and sentences were probed with a 2-minute delay measuring delayed recognition memory performance. Results revealed an advantage of the focused element in immediate but not in delayed retrieval. We found no effect of sentence type on the recognition of the two different probe types in WM performance. However, results pertaining to the memory accessibility of focus alternatives in delayed retrieval showed an interference effect resulting in a lower memory performance. We conclude that this effect is indirect evidence for the enhanced activation of focus alternatives. The present work is novel in two respects. First, no study has been conducted on the memory representation of focused elements and their alternatives in the case of the structurally marked Hungarian pre-verbal focus construction. Second, to our knowledge, this is the first study that investigates the focus representation accounts for WM and delayed recognition memory using the same stimuli and same measured variables. Since both experiments used exactly the same stimulus set, and they only differed in terms of the timing of recognition probes, the principle of ceteris paribus fully applied with respect to how we addressed our research question regarding the two different memory systems. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Beauty in the Context of Particular LivesPauliina Rautio (bio)IntroductionThere is a village in the north of Finland with some thirty inhabitants. While the villagers do not lead the idyllic lives that are sold as images to tourists, they also do not lead lives of depression, alcoholism, poverty, and seclusion—an image generated by research results from the likes of National Research and Development Centre for Welfare and Health. The ill-being (...) of rural northern villages is well documented in large-scale quantitative research,1 but qualitative research on the actual well-being, of what is already good and fulfilling, is scarce.In this paper I present a research project in education in which I have collected the data through a year-long correspondence with four participants from a small village. Letters in this correspondence were exchanged once a month in a way that everyone read everyone’s letters. I asked the participants to write about beauty. The aim of this research has been to find out what kind of place beauty, as defined by the participants themselves, holds in the their everyday lives. In this paper I will discuss some challenges of researching everyday beauty empirically. I will also concentrate on selected findings that highlight the importance of context in discussing experiences and use of beauty.Everyday life2 has been characterized in research by concepts such as “time,” “space,” “rhythm,” and “bodily movement.”3 These concepts embrace an idea of a continuum and refer to everyday life as subjectively experienced and actively engaged in. Everyday life is a contextual process but one that nevertheless defies definitions bound in time and space. This is because as subjectively experienced, it entails simultaneously the past, the present, and the future as necessary for the managing of it. By managing of everyday life I mean a practice that consists of constant reflection, evaluation, and steering, but one that we are mostly unaware of engaging [End Page 38] in. We are in a way creating our everyday lives as we go. This makes the everyday a subjective construct instead of an objectively definable unit such as “a Monday.” And so, instead of an attempt to tame the very vague notion of “everyday” as something universally shared,4 this research delves into particular individuals’ everyday lives as uniquely managed continuums. And to strike a rare positive chord to research on rural northern villages, I have chosen aesthetics, the notion of beauty in particular, as the vantage point to this making of everyday.I’m aligning with Ludwig Wittgenstein and quoting Katya Mandoki in stating that “beauty is a linguistic effect used by a particular subject to describe personal experiences and social conventions... a linguistic categorisation of a non-linguistic experience.”5 And despite the ambivalence that surrounds beauty as a concept in scholarly discussion, it is to be noted that it has remained in constant use in everyday conversation of common experience. When commonly used, “beautiful” still signals admiration, excellence, and that which is desirable.6 Beauty is therefore future-oriented, bringing about replication, distribution, and a wish to protect.7 As such a concept and a word of everyday use, “beauty” orients us to concentrate on the desirable in our lives at present. In doing so it guides us to evaluate this desirableness in light of the past and commits us to replicate and protect it for the future. Embedded in the use of the concept of beauty is thus a continuum of evaluating one’s relation to her surroundings. As beauty is not a quality of objects in themselves but an effect of the relation between the experiencing subjects and certain objects,8 it is not the objects of everyday beauty that I explore but the relation of particular people to their everyday life environments through ways of using and expressing beauty.The significance in thinking of beauty as something we create and use rather than something that exists objectively is in the realization that we can change what we find beautiful. Beauty as used by a particular subject is not fixed but changes and mirrors the changing of that subject herself. In realizing beauty this way, it becomes a... (shrink)

Presently, the State Grid Corporation of China has accumulated a large amount of maintenance records for power primary equipment. Unfortunately, most of these records are unstructured data which lead to difficultly analyze and utilize them. The emergence of natural language processing technology and deep learning methods provide a solution for unstructured text data. This paper proposes a progressive multitype feature fusion model to recognize Chinese named entity of unstructured maintenance records for power primary equipment. Firstly, the textual characteristics and (...) class='Hi'>word separation difficulties of maintenance records are analyzed, then 7 main entity categories of power technical terms from unstructured maintenance records are chosen, and 3452 maintenance records are labeled by these categories, which is so called EPE-MR training dataset. Secondly, the standard test reports, standard maintenance, and fault analysis reports for three types of power primary equipment are employed as corpus to train character embedding in order to obtain certain words representation ability of maintenance records. After that, progressive multilevel radicals feature extraction module is designed to get detailed and fine semantic information in a hierarchical manner. Further, radicals feature representation and character embedding are concatenated and sent to BiLSTM module to extract contextual information in order to improve Chinese entity recognition ability. Moreover, CRF is introduced to handle the dependencies among prediction labels and to output the optimal prediction sequence, which can easily obtain structured data of maintenance records. Finally, comparative experiments on public MSRA dataset, China People’s Daily corpus, and EPE-MR dataset are implemented, respectively, which show the effectiveness of the proposed method. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Reviewed by:Beyond Heaven and Earth: A Cognitive Theory of Religion by Gabriel LevyKevin SchilbrackBeyond Heaven and Earth: A Cognitive Theory of Religion. Gabriel Levy. Cambridge, MA: The MIT Press, 2022. 249 pp. $45.00 paperback; open access.The interdisciplinary field of religious studies includes both the humanities and social sciences in a tricky detente. Some religion scholars focus on interpreting texts, teachings, and rituals in an effort to grasp what religious (...) practitioners understand themselves to be doing. Other scholars want to move beyond the the practitioners’ views to create explanatory accounts of religion in terms of social power, psychological benefits, and modules in the evolved brain—causal accounts of which the practitioners might not be aware or that they might deny. Gabriel Levy argues that to develop consilience between the divergent efforts of the humanities and the sciences, the academic study of religion would be well served by developing a more adequate metaphysics that can do justice simultaneously to human behavior as moved both by subjective reasons and by material forces. Specifically, he recommends the “anomalous monism” of Donald Davidson. [End Page 98]According to this view, there is only one kind of reality, and this is a monist metaphysics that includes no nonmaterial or supernatural entities. However, this one kind of reality is “anomalous” in that the world we experience together permits two irreducible vocabularies, one that is physical and deterministic and another that is mental and includes free will. Davidson considered this two-sided approach Spinozistic (169), and Levy notes its similarities to Thomas Nagel’s “neutral monism” (8, 35, 50–51). In short, then, Levy is proposing to scholars of religion a non-reductive but science-friendly “pragmatist monism” (8) that would be congenial to many readers of this journal. Such a metaphysics would also be in line with the methodological naturalism that, for many, defines the legitimate scope of the academy. We might therefore consider this book an example of a philosophy of religious studies, or even a metaphysics for religious studies.An important feature of Davidson’s approach is that, on his account, semantic content is necessarily intersubjective and therefore non-nomological and irreducible to the physical. Imagine a parent offering their prelinguistic child a doll while asking, “Do you want your doll?” or pulling the child away from a neighbor’s dog while telling them, “You have to be careful around dogs.” Davidson argues that human beings learn the meaning of words and sentences in social exchanges like these as the listener makes an educated guess about the entities to which the other person is referring, a process that Davidson calls “triangulation.” The generation of meaning on this model depends on the human capacity for shared intentionality about things in the world. Davidson argues that having meaningful thoughts, even when alone, then requires that one has had intersubjective, “triangulated” experiences like these. As Levy says, “semantic content arises in immanent, contextual, enacted dialogue and conversation with other agents” (182). It follows that this Davidsonian approach insists on irreducible, non-eliminable mental categories such as meaning, belief, and reasons, now recast in terms of practical engagement with things rather than inner representations of them. Many in religious studies are critical of the field’s focus on subjective categories like these, but, as Levy points out, the meaning-generating and reason-giving subject on a Davidsonian model is necessarily a socially embedded self and not the free-floating, disembodied, or ahistorical self that is critiqued by post-structuralists like Michel Foucault (169–70).Levy introduces this model (ch. 1) and then explores several topics in its light. He proposes that beliefs about religious entities are a subset of imagining fictional entities, so that Mickey Mouse, Santa Claus, and Zeus are in the same cognitive category (ch. 2). He argues that there is a continuum between the human ability to interpret language and the ability of human beings and [End Page 99] other animals to interpret information in their natural environments (ch. 3). In the last three chapters, he connects his discussion to the Sefer Yitzirah, a medieval Jewish mystical “book of creation” that describes the cosmos as structured by language (ch. 4), to... (shrink)

Programming artificial intelligence to make fairness assessments of texts through top-down rules, bottom-up training, or hybrid approaches, has presented the challenge of defining cross-cultural fairness. In this paper a simple method is presented which uses vectors to discover if a verb is unfair or fair. It uses already existing relational social ontologies inherent in Word Embeddings and thus requires no training. The plausibility of the approach rests on two premises. That individuals consider fair acts those that they would (...) be willing to accept if done to themselves. Secondly, that such a construal is ontologically reflected in Word Embeddings, by virtue of their ability to reflect the dimensions of such a perception. These dimensions being: responsibility vs. irresponsibility, gain vs. loss, reward vs. sanction, joy vs. pain, all as a single vector. The paper finds it possible to quantify and qualify a verb as fair or unfair by calculating the cosine similarity of the said verb’s embedding vector against FairVec—which represents the above dimensions. We apply this to Glove and Word2Vec embeddings. Testing on a list of verbs produces an F1 score of 95.7, which is improved to 97.0. Lastly, a demonstration of the method’s applicability to sentence measurement is carried out. (shrink)

Numerous studies have investigated the neuro-cognitive mechanism of learning words in isolation or in semantic contexts recently. However, emotion as an important influencing factor on novel word learning has not been fully considered in the previous studies and how emotion affect word learning and the underlying neural mechanism have not been systematically investigated. 16 participants were trained to learn novel concrete or abstract words under negative, neutral and positive contextual emotions in continuous three days, and fufilled the testing (...) tasks in day1 and day3 during fMRI scanning. We compared the brain activations in day1 and day3 aming to investigate the role of contextual emotions in learning different types of words and the corresponding neural plasticity changes. Behaviorally, the performance for the words learned in negative context was lower than the neutral and positive contexts, which indicated that the contextual emotions had significant impact on novel word learning. Correspondingly, the functional plasticity changes of the right angular (AG), bilateral insula and anterior cingulate gyrus (ACC) induced by word learning were modulated by the contextual emotions. And the insula also was sensitive to the concreteness of the learned words. More importantly, the functional plasticity changes of left inferior frontal gyrus(L IFG) and left fusiform(L FG) were interactively influenced by the contextual emotions and words’ concreteness, suggesting that the contextual emotional information had a discriminable effect on different types of words in the neural mechanism level. These results demonstrate that the emotional information in contexts is inevitable for word learning, and the role of contextual emotions in brain plasticity for learning was discussed. (shrink)

Subjects exhibiting logical competence choices, for example, in Wason's selection task, are exhibiting an important skill. We take issue with the idea that this skill is individualistic and must be selected for at some different level than System 1 skills. Our case redraws System 1/2 boundaries, and reconsiders the relationship of competence model to skill.

Many successful sciences both serve and shape human ends. Conversely, the societies in which these sciences are practiced support the research and provide interpretive context. These mutual influences may result in a positive feedback loop that reinforces constitutive and contextual values, embedding them in scientific concepts: the ADHD concept is a case in point. In an ongoing process, social considerations fuel investigational choices and contexts for evaluating data. Scientific study forwards the feedback loop through the influence of investigative trends, by (...) directly and indirectly embedding values in data interpretation, and by core methodologies that heighten the contrast between ‘ADHD’ and ‘normal’. The resulting scientific conclusions embed value valences in the ADHD concept; social uptake of that valenced concept begins another round of interest in its implications and support of the science. The processes at work in the ADHD case are very general, so we should expect to see similar processes and results in other fields. (shrink)

Resisting Contextual Information: You Can't Put a Salient Meaning Down Two experiments support the graded salience hypothesis, which assumes that early processing involves distinct mechanisms-linguistic and contextual-that do not interact but run parallel. While contextual processes make up an integrative, top-down mechanism that benefits from linguistic and extra-linguistic information, the linguistic mechanism is modular. Using Vu et al.'s materials, Experiment 1 shows that the sentential position of a target word is crucial for the operation of the global, predictive mechanism, (...) whose effects, accumulated in prior discourse, mask lexical effects in final, but not in initial position. Experiment 2 shows that even in a sentential position that favors contextual effects, lexical access is not affected: Salient meanings are activated upon encounter of the lexical stimulus, regardless of contextual information to the contrary. Taken together, these findings argue against direct access models, which suggest that context can selectively activate the appropriate meaning, regardless of salience. (shrink)

Seth Yalcin has pointed out some puzzling facts about the behaviour of epistemic modals in certain embedded contexts. For example, conditionals that begin ‘If it is raining and it might not be raining, … ’ sound unacceptable, unlike conditionals that begin ‘If it is raining and I don’t know it, … ’. These facts pose a prima facie problem for an orthodox treatment of epistemic modals as expressing propositions about the knowledge of some contextually specified individual or group. This paper (...) develops an explanation of the puzzling facts about embedding within an orthodox framework. (shrink)

How should we account for the contextual variability of knowledge claims? Many philosophers favour an invariantist account on which such contextual variability is due entirely to pragmatic factors, leaving no interesting context-sensitivity in the semantic meaning of ‘know that.’ I reject this invariantist division of labor by arguing that pragmatic invariantists have no principled account of embedded occurrences of ‘S knows/doesn’t know that p’: Occurrences embedded within larger linguistic constructions such as conditional sentences, attitude verbs, expressions of probability, comparatives, and (...) many others, I argue, give rise to a threefold problem of embedded implicatures. (shrink)

The neural substrates of context effects in word perception are still largely unclear. Interhemispheric priming phenomena in word recognition, typically observed in normal subjects, are absent in commissurotomized patients. This suggests that callosal fibers may provide contextual integration. In addition, certain characteristics of human frontal cortical fields subserving sensorimotor learning, as investigated by positron emission tomography, provide evidence for contextual integration not confined to the visual system. This supports the notion of common aspects of cortical computations in different (...) cerebral areas. (shrink)

Contextual vocabulary acquisition (CVA) is the deliberate acquisition of a meaning for a word in a text by reasoning from context, where “context” includes: (1) the reader’s “internalization” of the surrounding text, i.e., the reader’s “mental model” of the word’s “textual context” (hereafter, “co-text” [3]) integrated with (2) the reader’s prior knowledge (PK), but it excludes (3) external sources such as dictionaries or people. CVA is what you do when you come across an unfamiliar word in your (...) reading, realize that you don’t know what it means, decide that you need to know what it means in order to understand the passage, but there is no one around to ask, and it is not in the dictionary (or you are too lazy to look it up). In such a case, you can try to figure out its meaning “from context”, i.e., from clues in the co-text together with your prior knowledge. Our computational theory of CVA—implemented in a the SNePS knowledge representation and reasoning system [28]—begins with a stored knowledge base containing SNePS representations of relevant PK, inputs SNePS representations of a passage containing an unfamiliar word, and draws inferences from these two (integrated) information sources. When asked to define the word, definition algorithms deductively search the resulting network for information of the sort that might be found in a dictionary definition, outputting a definition frame whose slots are the kinds of features that a definition might contain (e.g., class membership, properties, actions, spatio-temporal information, etc.) and whose slot-fillers contain information gleaned from the network [6–8,20,23,24]. We are investigating ways to make our system more robust, to embed it in a naturallanguage-processing system, and to incorporate morphological information. Our research group, including reading educators, is also applying our methods to the develop-. (shrink)

Learning depends on attention. The processes that cue attention in the moment dynamically integrate learned regularities and immediate contextual cues. This paper reviews the extensive literature on cued attention and attentional learning in the adult literature and proposes that these fundamental processes are likely significant mechanisms of change in cognitive development. The value of this idea is illustrated using phenomena in children's novel word learning.

In contextual cueing, previously encountered context tends to facilitate the detection of the target embedded in it than when the target appears in a novel context. In this study, we investigated whether the contextual cueing could develop at early time when the search display was presented briefly. In four experiments, participants searched for a target T in an array of distractor Ls. The results showed that with a rather short presentation time of the search display, participants were able to learn (...) the spatial context and speeded up their response time overall, with the learning effect lasting for a long period. Specifically, the contextual cueing effect was observed either with or without a mask after a duration of 300-ms presentation of the search display. Such a context learning under rapid presentation could not operate only with the local context information repeated, thus suggesting that a global context was required to guide spatial attention when the viewing time of the search display was limited. Overall, these findings indicate that contextual cueing might arise at an “early,” target selection stage and that the global context is necessary for the context learning under rapid presentation to function. (shrink)

Deliberate contextual vocabulary acquisition (CVA) is a reader’s ability to figure out a (not the) meaning for an unknown word from its “context”, without external sources of help such as dictionaries or people. The appropriate context for such CVA is the “belief-revised integration” of the reader’s prior knowledge with the reader’s “internalization” of the text. We discuss unwarranted assumptions behind some classic objections to CVA, and present and defend a computational theory of CVA that we have adapted to a (...) new classroom curriculum designed to help students use CVA to improve their reading comprehension. (shrink)

This article presents a new measure for intimate partner violence, the Gendered Violence in Partnerships Scale. The scale was developed in the Middle East with the aim to contribute to the global perspective on IPV by providing a contextual assessment tool for partner violence against women in violent-torn settings embedded in a patriarchal social structure. In an effort to generate a scale including IPV items relevant to the women of the population, a pragmatic step-wise procedure, with focus group discussions and (...) expert panels, was performed. The study’s analyses resulted in an 18-item checklist featuring four subscales of the GVPS that are based on a new typology of male-to-female partner violence presenting an alternative to the commonly used classification by type of abuse. Therein, dominating behaviors, existential threats, impulsive aggression, and aggravated physical assault were identified as reflective of the lived realities of women in the war-torn Middle East, which was confirmed in factor analysis. The scale’s psychometric properties were assessed with data from 1,009 displaced women in Iraq, and associations with measures of psychopathology were determined. Implications for IPV assessment and prevention possibilities in humanitarian contexts and beyond are discussed. (shrink)

This article explores the advantages of using a range of actual cases in doing political theory. This sort of approach clarifies what is at stake in alternative theoretical formulations, draws attention to the wisdom that may be embedded in existing practices, and encourages theorists to confront challenges they might otherwise overlook and to think through the implications of their accounts more fully.

The findings of our experiments showed that social network sites such as Google Plus, Facebook, and Twitter, have the ability to acquire knowledge about their users’ movements not only within SNSs but also beyond SNS boundaries, particularly among websites that embedded SNS widgets such as Google’s Plus One button, Facebook’s Like button, and Twitter’s Tweet button. In this paper, we analysed the privacy implication of such a practice from a moral perspective by applying Helen Nissenbaum’s decision heuristic derived from her (...) contextual integrity framework in order to answer the question of whether or not an online user’s privacy is being violated by this practice. (shrink)

Previous research on scalar implicature has primarily relied on meta-linguistic judgment tasks and found varying rates of such inferences depending on the nature of the task and contextual manipulations. This paper introduces a novel interactive paradigm involving both a production and a comprehension side and a precise conversational goal. The main research question is what is reliably communicated by some in this communicative setting, both when the quantifier occurs in unembedded and embedded positions. Our new paradigm involves an action-based task (...) from which participants’ interpretation of utterances can be inferred. It incorporates a game-theoretic design, thereby including a precise model to predict participants’ behaviour in the experimental context. Our study shows that embedded and unembedded implicatures are reliably communicated by some. We propose two cognitive principles that describe what can be left unsaid. In our experimental context, a production strategy based on these principles is more efficient than a strategy based on literal descriptions. (shrink)