Factors influencing the social perception of entrepreneurs in Spain: A quantitative analysis from secondary data.

The essential role that entrepreneurs play in the economy, while acknowledged in the academic context, is not always recognized socially. In the specific case of Spain, the profession has even been called into question by public institutions, which is highly detrimental to both the social image of entrepreneurs and the country's economy. Therefore, there is a need to identify factors that can improve this social image. This study aims to investigate one of these factors, specifically the effect of interest in economics. To do so, data from a large sample of 25,835 Spanish citizens from 2002-2022 were employed. The analysis was conducted using a combination of a neural network model and logistic regression. The conclusion of the study is that as interest in economics and business increases, the perception of entrepreneurs improves. Therefore, those individuals with less interest in economics tend to have a more negative view of this profession. This result opens up a potential avenue for enhancing the social image of entrepreneurs, as a higher interest in economics and business, which could be achieved through effective communication campaigns or basic education, leads to an improvement in perception.

Dunning-Kruger effect and flat-earthers: An exploratory analysis.

This article aims to analyze the factors influencing belief in a flat Earth. We focus on Spain, a country that sadly has some of the most relevant figures on this topic in the Spanish-speaking world. After a qualitative analysis of YouTube videos on the main channels on the subject, a survey was carried out on 1252 individuals. The results point to two conclusions. First is the presence of a considerable Dunning-Kruger effect among flat-earthers. There is a significant negative correlation between science literacy-overall and practically all its dimensions-and overconfidence in science in this group. The second, evaluated through a regression tree, confirms that the interaction of low scientific literacy and overconfidence is highly relevant in explaining the belief in a flat earth. Neither factor alone is determinant, but the combination of the two (low scientific literacy and high overconfidence) leads to high levels of flat earth belief.

Sentiment analysis of Lovecraft's fiction writings.

This paper, at the intersection of literary studies, computational literary analysis and psychology, analyzes Lovecraft's literary production throughout his career. Fifty-four writings from the period 1905-1935, which span almost all of his career as a fiction writer, have been studied by applying the computational techniques of sentiment analysis and following a methodology structured in three stages. In the first one, I analyzed each of the writings, in order to identify the relative percentage of emotion-inducing words according to Plutchik's Wheel of Emotions. The second phase of this process consisted of hierarchical cluster analysis to identify homogeneous groups of works. Finally, in the third step of the research, I conducted a statistical analysis. The results point to three different conclusions. First, the quantitative analysis confirms that there exists an intimate connection between the emotions of fear and sadness in Lovecraft's writings, which generates an intense emotion of despair. Second, the vast majority of his works can be grouped into two categories, each with a distinct pattern in terms of emotions. Finally, there seems to be a relationship between the identified categories and the evolution of Lovecraft's style; that is, there is a temporal evolution toward much darker works, which are dominated by negative emotions.

Spain is not different: teaching quantitative courses can also be hazardous to one's career (at least in undergraduate courses).

Student evaluations of teaching (SETs) have become a widely used tool for assessing teaching in higher education. However, numerous investigations have shown that SETs are subject to multiple biases, one of which is particularly relevant, namely, the area of knowledge to which the subject belongs. This article aims to replicate the article by Uttl & Smibert (2017, https://doi.org/10.7717/peerj.3299) in a different educational context to verify whether the negative bias toward instructors who teach quantitative courses found by the authors in the US also appears in the Spanish university system. The study was conducted at the Business and Law School of the Universidad Pontificia Comillas, a private Spanish university, using two different samples. First, we analyzed undergraduate courses using a sample of 80,667 SETs in which 2,885 classes (defined as a single semester-long course taught by an individual instructor to a specific group of students), 488 instructors, and 322 different courses were evaluated over a time period of four academic years (2016/2017-2019/2020). Second, in the same period, 16,083 SETs corresponding to master's degree courses were analyzed, which involved the study of 871 classes, 275 instructors, and 155 different courses. All the data included in the analysis were obtained from official university surveys developed by a team of professionals specialized in teaching quality responsible for ensuring the reliability of the information. At the degree level, the results show that despite the considerable cultural and temporal difference between the samples, the results are very similar to those obtained by Uttl & Smibert (2017, https://doi.org/10.7717/peerj.3299); i.e., professors teaching quantitative courses are far more likely to obtain worse SETs than instructors in other areas. There are hardly any differences at the master's degree level, regardless of whether nearly 75% of master's degree instructors also teach at the undergraduate level. This leads us to three different conclusions. (1) Evidence suggests that the reason for these differences is not due to faculty teaching quantitative courses being less effective than faculty teaching in some other fields. Our results indicate that the same instructor is evaluated very differently depending on whether he or she teaches at the undergraduate or master's level. (2) It is essential to avoid comparisons of SETs between different areas of knowledge, at least at the undergraduate level. (3) A significant change in the use and interpretation of SETs is imperative, or its replacement by other evaluation mechanisms should be considered. If this does not occur, it is possible that in the future, there will be an adverse selection effect among professors of quantitative methods; i.e., only the worst professionals in quantitative methods will opt for teaching since the good professionals will prefer other jobs.