Hubris-Humility Effect and Domain-Masculine Intelligence Type in Czech Republic

Czech adults completed a self-assessed intelligence measure that yielded a score on domainmasculine intelligence (DMIQ), a composite of mathematical/logical and spatial intelligences. They also completed a sex role inventory. The sex of the participants but not their sex role was related to DMIQ. There was a positive relationship between masculinity and DMIQ, but only for males. Cultural issues in self assessed intelligence and limitations of this study are considered

The role of gender, task success probability estimation and scores as predictors of the domain-masculine intelligence type (DMIQ)

This paper reports a study aimed at understanding correlates of self-estimated intelligence. Participants twice estimated their mathematical and spatial intelligence (called domain-masculine intelligence type: DMIQ) on a normal distribution, before and after taking ability tests. They completed a number of short numerical and logical ability tests after which they estimated their performance at a similar, more difficult task. Males gave higher estimates than females and did better on the tests. As predicted their estimates of their DMIQ reduced on the second occasion after testing. Gender, task score and estimated performance were all significant predictors of both DMIQ scores. Task confidence was the best predictor of both before and after test estimates, over and above gender and test score, explaining 17% and 23% of variance, respectively. This is explained in terms of Dweck's (2007) mindset theory and Eccles and Wigfield's (2002) motivation theory. Results are discussed in terms of the literature on self-estimated intelligence and stereotype threat

Hubris and Humility Effect and the Domain-Masculine Intelligence Type in Two Countries: Colombia and the UK

Spanish-speaking Colombian (n = 50) and English-speaking British (N = 52) adults completed a self-assessed intelligence measure that yielded a score on domain-masculine intelligence (DMIQ), a composite of mathematical/logical and spatial intelligences. They also completed a Sex Role inventory in order to establish their masculinity and femininity. Males in both countries gave significantly higher self-estimates (Colombia: Males 110.36, Females 100.75, d = .94; England: Males 114.37, Females 105.75, d = .86; both p < .01) than females but sex role was note related to DMIQ. However there was a positive relationship between masculinity and DMIQ (r = .45, r = .39, p < .01), but only for males. Cultural issues in self-assessed intelligence and limitations, particularly sample size of this exploratory study are considered

Reconstitution of the immune system after hematopoietic stem cell transplantation in humans

Hematopoietic stem cell transplantation is associated with a severe immune deficiency. As a result, the patient is at high risk of infections. Innate immunity, including epithelial barriers, monocytes, granulocytes, and NK cells recovers within weeks after transplantation. By contrast, adaptive immunity recovers much slower. B- and T-cell counts normalize during the first months after transplantation, but in particular, T-cell immunity may remain impaired for years. During the last decade, much of the underlying mechanisms have been identified. These insights may provide new therapies to accelerate recover

Global Characterization of Protein Secretion from Human Macrophages Following Non-canonical Caspase-4/5 Inflammasome Activation

Gram-negative bacteria are associated with a wide spectrum of infectious diseases in humans. Inflammasomes are cytosolic protein complexes that are assembled when the cell encounters pathogens or other harmful agents. The non-canonical caspase-4/5 inflammasome is activated by Gram-negative bacteria-derived lipopolysaccharide (LPS) and by endogenous oxidized phospholipids. Protein secretion is a critical component of the innate immune response. Here, we have used label-free quantitative proteomics to characterize global protein secretion in response to non-canonical inflammasome activation upon intracellular LPS recognition in human primary macrophages. Before proteomics, the total secretome was separated into two fractions, enriched extracellular vesicle (EV) fraction and rest-secretome (RS) fraction using size-exclusion centrifugation. We identified 1048 proteins from the EV fraction and 1223 proteins from the RS fraction. From these, 640 were identified from both fractions suggesting that the non-canonical inflammasome activates multiple, partly overlapping protein secretion pathways. We identified several secreted proteins that have a critical role in host response against severe Gram-negative bacterial infection. The soluble secretome (RS fraction) was highly enriched with inflammation-associated proteins upon intracellular LPS recognition. Several ribosomal proteins were highly abundant in the EV fraction upon infection, and our data strongly suggest that secretion of translational machinery and concomitant inhibition of translation are important parts of host response against Gram-negative bacteria sensing caspase-4/5 inflammasome. Intracellular recognition of LPS resulted in the secretion of two metalloproteinases, a disintegrin and metalloproteinase domain-containing protein 10 (ADAM10) and MMP14, in the enriched EV fraction. ADAM10 release was associated with the secretion of TNF, a key inflammatory cytokine, and M-CSF, an important growth factor for myeloid cells probably through ADAM10-dependent membrane shedding of these cytokines. Caspase-4/5 inflammasome activation also resulted in secretion of danger-associated molecules S100A8 and prothymosin- in the enriched EV fraction. Both S100A8 and prothymosin- are ligands for toll-like receptor 4 recognizing extracellular LPS, and they may contribute to endotoxic shock during non-canonical inflammasome activation.Peer reviewe

Unsupervised Selective Rationalization with Noise Injection

A major issue with using deep learning models in sensitive applications is that they provide no explanation for their output. To address this problem, unsupervised selective rationalization produces rationales alongside predictions by chaining two jointly-trained components, a rationale generator and a predictor. Although this architecture guarantees that the prediction relies solely on the rationale, it does not ensure that the rationale contains a plausible explanation for the prediction. We introduce a novel training technique that effectively limits generation of implausible rationales by injecting noise between the generator and the predictor. Furthermore, we propose a new benchmark for evaluating unsupervised selective rationalization models using movie reviews from existing datasets. We achieve sizeable improvements in rationale plausibility and task accuracy over the state-of-the-art across a variety of tasks, including our new benchmark, while maintaining or improving model faithfulness.Comment: Accepted to ACL 202

The hubris and humility effect and the domain-masculine intelligence type: exploration of determinants of gender differences in self-estimation of ability

This thesis explores the potential determinants of gender differences in self-estimated intelligence. In particular, it addresses the determinants of gender differences in the ‘domain-masculine intelligence type’ that is expected to yield the most significant gender differences in the self-estimated intelligence model (SEI). Equally, it sets to confirm the occurrence of the ‘hubris-humility effect’ (HHE), i.e. male overestimation and female underestimation of cognitive abilities, specifically in the above intelligence type. The thesis contains eight chapters, ten correlational studies and five experimental studies. The thesis is divided in two sections. Section one contains the ten correlational studies and section two the five experimental studies. All studies are independent but related. Chapter one contains a review of the relevant literature. It is divided into three sub-sections: overview, intelligence and hubris-humility effect (HHE) and domain-masculine intelligence type (DMIQ): gender differences in self-estimated intelligence. Chapter two (Studies 1 and 2) introduces the domain-masculine intelligence type and demonstrates it is the most sensitive indicator of gender differences in the SEI model. HHE is shown to be the most pronounced and confined to occurring on DMIQ. Equally, gender is shown as the best predictor of DMIQ, over and above a number of other demographic variables. Chapter three (Studies 3 to 5) sets to validate the occurrence of HHE on DMIQ, while it introduces psychometric intelligence (‘g’) and implicit beliefs about intelligence as possible determinants of DMIQ. Studies 3 and 4 examine the role ‘g’, as measured by fluid (Gf) and crystallised (Gc) intelligence tests, play in DMIQ. Results confirm the occurrence of HHE on DMIQ and reveal significant gender differences in Gf and Gc, with medium and large effect sizes. Gender is shown to influence the relationship between ‘g’ and DMIQ. Contrary to prediction, a psychometric intelligence measure (Gf), and not gender, is the best predictor of DMIQ. Implicit beliefs about intelligence play no role in the prediction of DMIQ. Study 5 adds gender identity variables, i.e. masculinity and femininity, and self-construct measures, i.e. self-esteem and self-control, to Gf and Gc, as possible predictors of DMIQ. Results validate the existence of HHE on DMIQ and confirm gender as the best predictor DMIQ, over and above ‘g’, gender identity variables and self-construct measures. Chapter four (Studies 6 and 7) examines the role gender identity, i.e. masculinity and femininity, affect measures, i.e. positive and negative affect, and self-constructs, i.e. self-esteem and self-control, play as potential determinants of DMIQ. Both studies confirm the existence of HHE on DMIQ. Study 6 confirms gender as the best and only predictor of DMIQ. Study 7 affirms masculinity as the best predictor of the intelligence type, followed by gender. Chapter five (Studies 8 and 9) examines the role of culture in DMIQ and its impact on the existence of HHE on DMIQ. Gender identity variables are also included to validate the earlier findings and to explore the role masculinity plays as a predictor of DMIQ, in three distinct cultures. Study 8 was conducted in Czech Republic and Study 9 in Colombia and United Kingdom. Results confirm the occurrence of HHE on DMIQ in all three cultures, with medium effect size for the Czech sample and large effect sizes for the Colombian and British samples. Gender is shown to influence the relationship between gender identity variables and DMIQ. Contrary to prediction, masculinity and not gender, is the best predictor of DMIQ in the Czech Republic sample. In the Colombian sample, none of the entered variables significantly contributes to the prediction of DMIQ. In the British sample, gender is affirmed as the best predictor of DMIQ, followed by masculinity. The results suggest that culture influences the composition of DMIQ determinant(s). Chapter six (Study 10) explores the role of DMIQ in a precocious sample, i.e. members of Mensa UK. It also sets to validate the occurrence of HHE prevails on DMIQ in a population that is knowledgeable about intelligence as well as aware of its own intellectual superiority. Beliefs about intelligence and gender identity variables are also included to explore whether they will play a role in the prediction of the intelligence type. The results confirm the existence of HHE on DMIQ in this precocious population, providing additional evidence for the degree of embeddedness and impact of HHE on highly gifted individuals. Gender is confirmed as the only and best predictor of DMIQ. Chapter seven (Studies 11 to 15) contains five independent experimental studies. Study 14 was conducted with three independent samples to test three varying task-confidence conditions. The results of the three individual conditions are reported in the Appendix, while the combined total results are reported in Study 14. The five experiments consist of repeated measurement of DMIQ and a psychometric task (TCAP) that also includes task-success probability probes (TSP). Participants are asked to estimate DMIQ before and after the task. The task contains numerical, reasoning, and crystallised intelligence items as well as task-success or task-confidence probes. The number of the psychometric items and probes are manipulated per experiment to assess their impact on the results. As such, the task is expected to be gender-stereotype inducing. As in the correlational studies, HHE is predicted to occur in the pre- and posttask DMIQ conditions. Results of all five studies validate the existence of HHE on DMIQ1 and DMIQ2, with medium to very large effect sizes. Likewise, a significant decrease in the DMIQ estimates is observed in all five studies, with small to medium effect sizes. In addition, male advantage is confirmed on the psychometric task and the task-success probes. Gender differences in TCAP are observed in Studies 11, 12 and 15, with males correctly solving significantly more psychometric problems than females. Equally, gender differences in TSP occur in Studies 11, 12 and 13, with males providing significantly higher task-confidence answers than females. To validate the earlier results, gender is expected as the best predictor of DMIQ1 and DMIQ2. Results reveal that gender is the best predictor of DMIQ1 in three out of five studies and in two out of five studies in DMIQ2. Unexpectedly, task-success probes are twice the best predictor of DMIQ1 and three times the best predictor of DMIQ2. Moreover, gender influences the relationship between TPS and DMIQ1 and DMIQ2 in all five studies. Equally, gender influences the relationship between TCAP and DMIQ1 and DMIQ2, in all but one analysis. Surprisingly, the DMIQ1 and DMIQ2 estimates that are provided by participants in the three task-success probability groups, i.e. low, average and high, are startlingly accurate, with the exception of Study 14. That is, low DMIQ estimates are provided by participants with low task-success confidence, average estimates are provided by participants with average task-success confidence and the highest DMIQ estimates by individuals with highest task-success confidence. Results for TCAP are complex and less accurate. Yet, for both TSP and TCAP, males provide significantly higher DMIQ1 and DMIQ2 estimates than females, providing further evidence for the occurrence of male hubris in the self-estimation of ability process. Chapter eight presents a brief summary of results and conclusions of this research. Equally, limitations of this research are discussed and a number of future research recommendations provided. The appendix includes the three individual condition studies of Study 14; that is Studies 14A, 14B and 14C. The TCAP and TSP overviews for Studies 11 to 15 are also included. Finally, Study 16 that uses the combined sample made of the fifteen individual study samples (N = 2292) is integrated. Study 16 tests the main objectives of this thesis through previously used hypotheses and as such provides a summary overview of the results. All main objectives of this thesis are corroborated