On the Quantum-like Contextuality of Ambiguous Phrases

Language is contextual as meanings of words are dependent on their contexts. Contextuality is, concomitantly, a well-defined concept in quantum mechanics where it is considered a major resource for quantum computations. We investigate whether natural language exhibits any of the quantum mechanics' contextual features. We show that meaning combinations in ambiguous phrases can be modelled in the sheaf-theoretic framework for quantum contextuality, where they can become possibilistically contextual. Using the framework of Contextuality-by-Default (CbD), we explore the probabilistic variants of these and show that CbD-contextuality is also possible

Analysing Ambiguous Nouns and Verbs with Quantum Contextuality Tools

Psycholinguistic research uses eye-tracking to show that polysemous words are disambiguated differently from homonymous words, and that ambiguous verbs are disambiguated differently than ambiguous nouns. Research in Compositional Distributional Semantics uses cosine distances to show that verbs are disambiguated more efficiently in the context of their subjects and objects than when on their own. These two frameworks both focus on one ambiguous word at a time and neither considers ambiguous phrases with two (or more) ambiguous words. We borrow methods and measures from Quantum Information Theory, the framework of Contextuality-by-Default and degrees of contextual influences, and work with ambiguous subject-verb and verb-object phrases of English, where both the subject/object and the verb are ambiguous. We show that differences in the processing of ambiguous verbs versus ambiguous nouns, as well as between different levels of ambiguity in homonymous versus polysemous nouns and verbs can be modelled using the averages of the degrees of their contextual influences

Contextuality and noncontextuality measures and generalized Bell inequalities for cyclic systems

Cyclic systems of dichotomous random variables have played a prominent role in contextuality research, describing such experimental paradigms as the Klyachko-Can-Binicioglu-Shumovsky, Einstein-Podolsky-RosenBell, and Leggett-Garg ones in physics, as well as conjoint binary choices in human decision making. Here, we understand contextuality within the framework of the Contextuality-by-Default (CbD) theory, based on the notion of probabilistic couplings satisfying certain constraints. CbD allows us to drop the commonly made assumption that systems of random variables are consistently connected (i.e., it allows for all possible forms of "disturbance" or "signaling" in them). Consistently connected systems constitute a special case in which CbD essentially reduces to the conventional understanding of contextuality. We present a theoretical analysis of the degree of contextuality in cyclic systems (if they are contextual) and the degree of noncontextuality in them (if they are not). By contrast, all previously proposed measures of contextuality are confined to consistently connected systems, and most of them cannot be extended to measures of noncontextuality. Our measures of (non)contextuality are defined by the L-1-distance between a point representing a cyclic system and the surface of the polytope representing all possible noncontextual cyclic systems with the same single-variable marginals. We completely characterize this polytope, as well as the polytope of all possible probabilistic couplings for cyclic systems with given single-variable marginals. We establish that, in relation to the maximally tight Bell-type CbD inequality for (generally, inconsistently connected) cyclic systems, the measure of contextuality is proportional to the absolute value of the difference between its two sides. For noncontextual cyclic systems, the measure of noncontextuality is shown to be proportional to the smaller of the same difference and the L-1-distance to the surface of the box circumscribing the noncontextuality polytope. These simple relations, however, do not generally hold beyond the class of cyclic systems, and noncontextuality of a system does not follow from noncontextuality of its cyclic subsystems

A QP Framework: A Contextual Representation of Agents’ Preferences in Investment Choice

Contextual decisions and beliefs and their impact upon market outcomes are at the core of research in behavioural finance. We describe some of the notable probabilistic fallacies that underpin investor behaviour and the consequent deviation of asset prices from the rational expectations equilibrium. In real financial markets, the complexity of financial products and the surrounding ambiguity calls for a more general formalization of agents belief formation than offered by the standard probability theory and dynamic models based on classical stochastic processes. The main advantage of quantum probability (QP) is that it can capture contextuality of beliefs through the notion of non-commuting prospect observables. QP has the potential to model myopia in asset return evaluation, as well as inter-asset valuation. Moreover, the interference term of the agents’ comparison state can provide a quantitative description of their vacillating ambiguity perception characterized by non-additive beliefs of agents. Some of the implications of non-classicality in beliefs for the composite market outcomes can also be modelled with the aid of QP. As a final step we also discuss the contributions of the growing body of psychological studies that reveal a true (quantum type) contextuality in human preference statistics showing that the classical probability theory is too restrictive to capture the very strong non-classical correlations between preference outcomes and beliefs

Genomic analysis of early SARS-CoV-2 variants introduced in Mexico

The coronavirus disease 2019 (COVID-19) pandemic has affected most countries in the world. Studying the evolution and transmission patterns in different countries is crucial to enabling implementation of effective strategies for disease control and prevention. In this work, we present the full genome sequence for 17 SARS-CoV-2 isolates corresponding to the earliest sampled cases in Mexico. Global and local phylogenomics, coupled with mutational analysis, consistently revealed that these viral sequences are distributed within 2 known lineages, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineage A/G, containing mostly sequences from North America, and lineage B/S, containing mainly sequences from Europe. Based on the exposure history of the cases and on the phylogenomic analysis, we characterized 14 independent introduction events. Additionally, three cases with no travel history were identified. We found evidence that two of these cases represented local transmission cases occurring in Mexico during mid-March 2020, denoting the earliest events described for the country. Within this local transmission cluster, we also identified an H49Y amino acid change in the Spike protein. This mutation represents a homoplasy occurring independently through time and space and may function as a molecular marker to follow any further spread of these viral variants throughout the country. Our results provide a general picture of the SARS-CoV-2 variants introduced at the beginning of the outbreak in Mexico, setting the foundation for future surveillance efforts

Latina Birth Outcomes in California: Not so Paradoxical

OBJECTIVES: To investigate Latina-White differences in birth outcomes in California from 2003 to 2010, looking for evidence of the often-cited “Latina paradox” and assessing the possible role of socioeconomic factors in observed differences. METHODS: Using statewide-representative data from the California Maternal and Infant Health Assessment, an annual population-based postpartum survey, we compared rates of preterm birth (PTB) and low birth weight (LBW) in five groups: U.S.-born non-Latina Whites (“Whites”), U.S.-born Mexican–Americans, U.S.-born non-Mexican Latinas, Mexican immigrants, and non-Mexican Latina immigrants. Logistic regression models examined the relative likelihood of PTB and LBW for women in each Latina subgroup compared with Whites, before and after adjustment for socioeconomic and other covariates. RESULTS: In unadjusted analyses, women in each Latina subgroup appeared more likely than White women to have PTB and LBW, although the increased likelihood of LBW among Mexican immigrants was statistically non-significant. After adjustment for less favorable socioeconomic characteristics among Latinas compared with Whites, observed differences in the estimated likelihoods of PTB or LBW for Latina subgroups relative to Whites were attenuated and (with the exception of PTB among U.S.-born Mexican Americans) no longer statistically significant. CONCLUSIONS: We found no evidence of a “Latina paradox” in birth outcomes, which some have cited as evidence that social disadvantage is not always health-damaging. As observed in several previous studies, our findings were non-paradoxical: consistent with their socioeconomic disadvantage, Latinas had worse birth outcomes than non-Latina White women. Policy-makers should not rely on a “Latina paradox” to ensure good birth outcomes among socioeconomically disadvantaged Latina women