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Using Schein’s Descriptive Index (SDI), this paper aims to first examine gender role stereotypes and requisite managerial characteristics among Irish business students over a 10-year period. Then, the paper investigates whether there have been changes in gender role stereotypes during this period and subsequently unpack the reasons behind any changes recorded.

In total, 1,124 students from the same business student population rated men, women and managers in general, using SDI. Data was collected first during the academic year 2008–2009 and again in 2018–2019 to determine stability or change in gender role stereotypes and requisite managerial characteristics. Intraclass correlation coefficients scores were computed to determine the relationship between gender and requisite managerial characteristics and identify differences and similarities between the two samples. To explore the content of gender stereotypes, an examination of the specific descriptive items was conducted by performing a factorial analysis using Duncan’s Multiple Range Test. Finally, the authors adapted the scales developed by Duehr and Bono (2006) to determine whether broad gender stereotypic characteristics with respect to communal and agentic, attributed to men, women and managers, differ by sample.

The overall findings indicate changes in the extent of gender role stereotyping of the managerial role among the male cohorts studied. The subsequent analysis of the descriptive items identified that the change among the male cohort is due to the levels of agency they perceive women to now possess.

The authors contribute to the literature on both gendered and managerial stereotypes by showing changes in the pro-male stereotype of the managerial role and contribute to the existing debate on a shift towards a more androgynous view of leadership.

These findings help understand the content of gender role stereotypes that recent graduates bring with them to their first job post-graduation. The observed changes in the level of agency ascribed to women by their male counterparts could prove to be an important step forward for women’s advancement to managerial positions.

The findings indicate that both male and female cohorts in Sample 2 perceived men and women in general to possess the same levels of communal and agentic traits as their managerial counterparts.

This paper aims to examine the impact of problem-solving activities, emotional experiences and contextual and personal factors on learning from dealing with software-related problems in everyday office work.

To measure the use of problem-solving activities, emotional experiences and the contextual factors of problem characteristics and learning in situ, a research diary was used. To measure team psychological safety (contextual factor) and personal factors, including the Big Five personality traits, occupational self-efficacy and technology self-efficacy, the authors administered a self-report questionnaire. In sum, 48 students from a software company in Germany recorded 240 diary entries during five working days. The data was analysed using multilevel analysis.

Results revealed that asking others and using information from the internet are positive predictors of self-perceived learning from a software-related problem, while experimenting, which was the most common activity, had a negative effect on learning. Guilt about the problem was positively related to learning while working in the office (as opposed to remote work), and feeling irritated/annoyed/angry showed a negative effect. Surprisingly, psychological safety had a negative effect on perceived learning.

Major limitations of the study concern the convenience sample and the disregard for the sequence of the activities.

This study contributes to the limited empirical evidence on employees’ problem-solving activities and informal workplace learning in the software context. To overcome the shortcomings of previous studies using retrospective assessments and in-lab observations, this study uses the diary method to investigate in situ.

Although not yet fully defined, natural wine represents a sector that has gained the widespread attention of final consumers and, therefore, also of the restaurant world, because of its promise of sustainability. The objective of this paper is to understand Italian haute cuisine's interest in natural wine, with the aim of analysing what qualifies this product as sustainable.

After introducing a theoretical framework based on the concept of natural wine, a brief paragraph is dedicated to consumer preferences; subsequently, the analysis focusses on a questionnaire given to restaurateurs to determine the impact that natural wine has had in the Italian context. The results try to identify the importance that restaurateurs give to the characteristics of natural wine and their propensity for using such wine in their own businesses.

The analysis, conducted on a sample of medium-high range restaurants, highlights their strong interest in natural wine, as a result of the final consumers' attitude towards wine with characteristics attributable to sustainability. The positive perception by restaurateurs is similar across Italy, both geographically and in terms of the size of the restaurant.

The originality of the work is the focus on the world of restaurants. To date, the literature on natural wine remains embryonic and always refers to the final consumer. This research is the first step in a broader study that will involve a greater number of restaurants, extending beyond Italy to all of Europe, with the aim of understanding the real development potential of natural wine.

In the new development stage of comprehensively building a socialist modern state, it is imperative to adhere to the guidance of Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era, comprehensively summarize China's practical experiences in economic development, strengthen research on capital issues, construct theories of socialist political economy with Chinese characteristics regarding capital and provide scientific theoretical guidance for further promoting the positive role of various types of capital while preventing and overcoming their negative effects, which is a major theoretical issue and a glorious task for the theoretical and economic circles in China.

From the perspective of Marx's theory on capital and historical development, modern capital represents the organizational mode of socialized mass production and market economy. It serves as both the economic foundation of bourgeois society and a tool for socialist economic development.

The market economy represents an inevitable historical stage and form of socialist economic development, necessitating the adoption of capital as an organizational form within socialist economies.

The utilization of capital to advance a socialist economy is a remarkable achievement by the CPC and Chinese people, representing a significant innovation in both theory and practice. The role of capital is inherently dual under any social condition. In the context of a socialist system, capital can play a positive role effectively, and its behavior can be guided and regulated correctly to curb its negative or even destructive impact.

This mixed-method, collaborative study investigated parents’ perceptions of STEM (Science, Technology, Engineering and Mathematics) learning through use of STEM kits specifically designed for in-home use by parents and preschool-age children.

Parents with a child attending a community-based childhood development center and ranging in age from three to four were invited to participate. Data were analyzed for the participants’ surveys, which were completed at two different times (pre and post) for this study.

After utilizing the STEM materials with their child over a two-week period, the parents’ perceptions of STEM content changed. The results indicate that regardless of the at-home STEM materials, positive outcomes for their child occurred, including the likelihood that their child would pursue additional STEM opportunities.

With a small sample size and a short timeframe for conducting the study, the results lack generalizability. The findings add information about the effectiveness of STEM materials for preschoolers while providing insight into educational opportunities in home environments.

As the nation addresses workforce shortages in many areas, including STEM, rethinking STEM education during the first five years is important. The more opportunities for young children to engage in meaningful STEM, the greater the potential to pique interest and develop critical thinking skills.

Sarcasm is a linguistic expression that usually carries the opposite meaning of what is being said by words, thus making it difficult for machines to discover the actual meaning. It is mainly distinguished by the inflection with which it is spoken, with an undercurrent of irony, and is largely dependent on context, which makes it a difficult task for computational analysis. Moreover, sarcasm expresses negative sentiments using positive words, allowing it to easily confuse sentiment analysis models. This paper aims to demonstrate the task of sarcasm detection using the approach of machine and deep learning.

For the purpose of sarcasm detection, machine and deep learning models were used on a data set consisting of 1.3 million social media comments, including both sarcastic and non-sarcastic comments. The data set was pre-processed using natural language processing methods, and additional features were extracted and analysed. Several machine learning models, including logistic regression, ridge regression, linear support vector and support vector machines, along with two deep learning models based on bidirectional long short-term memory and one bidirectional encoder representations from transformers (BERT)-based model, were implemented, evaluated and compared.

The performance of machine and deep learning models was compared in the task of sarcasm detection, and possible ways of improvement were discussed. Deep learning models showed more promise, performance-wise, for this type of task. Specifically, a state-of-the-art model in natural language processing, namely, BERT-based model, outperformed other machine and deep learning models.

This study compared the performance of the various machine and deep learning models in the task of sarcasm detection using the data set of 1.3 million comments from social media.

Digital resources such as smart applications reviews and online feedback information are important sources to seek customers’ feedback and input. This paper aims to help government entities gain insights on the needs and expectations of their customers. Towards this end, we propose an aspect-based sentiment analysis hybrid approach that integrates domain lexicons and rules to analyse the entities smart apps reviews. The proposed model aims to extract the important aspects from the reviews and classify the corresponding sentiments. This approach adopts language processing techniques, rules, and lexicons to address several sentiment analysis challenges, and produce summarized results. According to the reported results, the aspect extraction accuracy improves significantly when the implicit aspects are considered. Also, the integrated classification model outperforms the lexicon-based baseline and the other rules combinations by 5% in terms of Accuracy on average. Also, when using the same dataset, the proposed approach outperforms machine learning approaches that uses support vector machine (SVM). However, using these lexicons and rules as input features to the SVM model has achieved higher accuracy than other SVM models.

It's hard to envision a system more global and more integrated than research. Many stakeholders affect and are affected by changes in the research ecosystem; the ecosystem differs in significant ways across the globe and between researchers, institutions and fields of study; and there are many questions that exclusive action can't address. There are also broad ecosystem-level questions that need answering. For these reasons alone, global approaches to reform are needed.

The first step in this exploration isn't to start looking for “solutions”, but to develop a better understanding of how our needs and interests overlap. By identifying the broad contours of common ground in this conversation, we can build the guardrails and mileposts for our collaborative efforts and then allow the finer-grained details of community-developed plans more flexibility and guidance to evolve over time.

What are these overlapping interests? First, the people in this community share a common motive – idealism – to make research better able to serve the public good. We also share a common desire to unleash the power of open to improve research and accelerate discovery; we are all willing to fix issues now instead of waiting for market forces or government intervention to do this for us; and we want to ensure that everyone everywhere has equitable access to knowledge.

There is also very broad agreement in this community about which specific problems in scholarly communication need to be fixed and why, and well as many overlapping beliefs in this community. OSI participants have concluded that four such beliefs best define our common ground: (1) research and society will benefit from open done right; (2) successful solutions will require broad collaboration; (3) connected issues need to be addressed, and (4) open isn't a single outcome, but a spectrum.

OSI has been observing and debating the activity in scholarly communication since late 2014 with regard to understanding possible global approaches and solutions for improving the future of open research. While the COVID-19 pandemic has made the importance of open science abundantly clear, the struggle to achieve this goal (not just for science but for all research) has been mired in a lack of clarity and urgency for over 20 years now, mostly stalling on the tension between wanting more openness but lacking realistic solutions for making this happen on a large scale with so many different stakeholders, needs and perspectives involved.

Underlying this tension is a fundamental difference in philosophy: whether the entire scholarly communication marketplace, driven by the needs and desires of researchers, should determine what kind of open it wants and needs; or whether this marketplace should be compelled to adopt open reform measures developed primarily by the scholarly communication system's main billpayers-funders and libraries. There is no widespread difference of opinion in the community whether open is worth pursuing. The debate is mostly over what specific open solutions are best, and at what pace open reforms should occur.

OSI has proposed a plan of action for working together to rebuild the future of scholarly communication on strong, common ground foundation. This plan – which we're referring to as Plan A – calls for joint action on studies, scholarly communication infrastructure improvement, and open outreach/education. Plan A also calls for working together with UNESCO to develop a unified global roadmap for the future of open, and for striving to ensure the community's work in this space is researcher-focused, collaborative, connected (addressing connected issues like peer review), diverse and flexible (no one-size-fits-all solutions), and beneficial to research. UNESCO's goal is to finish its roadmap proposal by early 2022.

For a full discussion of OSI's common ground recommendations, please see the Plan A website at http://plan-a.world.

To elaborate the nature of fact-checking in the domain of political information by examining how fact-checkers assess the validity of claims concerning the Russo-Ukrainian conflict and how they support their assessments by drawing on evidence acquired from diverse sources of information.

Descriptive quantitative and qualitative content analysis of 128 reports written by the fact-checkers of Snopes – an established fact-checking organisation – during the period of 24 February 2022 – 28 June, 2023. For the analysis, nine evaluation grounds were identified, most of them inductively from the empirical material. It was examined how the fact-checkers employed such grounds while assessing the validity of claims and how the assessments were bolstered by evidence acquired from information sources such as newspapers.

Of the 128 reports, the share of assessments indicative of the invalidity of the claims was 54.7%, while the share of positive ratings was 26.7%. The share of mixed assessments was 15.6%. In the fact-checking, two evaluation grounds, that is, the correctness of information and verifiability of an event presented in a claim formed the basis for the assessment. Depending on the topic of the claim, grounds such as temporal and spatial compatibility, as well as comparison by similarity and difference occupied a central role. Most popular sources of information offering evidence for the assessments include statements of government representatives, videos and photographs shared in social media, newspapers and television programmes.

As the study concentrated on fact-checking dealing with political information about a specific issue, the findings cannot be extended to concern the fact-checking practices in other contexts.

The study is among the first to characterise how fact-checkers employ evaluation grounds of diverse kind while assessing the validity of political information.

This research finds out to what extent companies’ names are influenced by the place’s attributes versus the official branding policies of a place and, consequently, whether and how local companies “buy into” the place’s strategies put forth by official bodies.

This paper is both conceptual and empirical, as a mixed quantitative and interpretive approach is used. The companies’ names of a tourist industry (the tour and guiding companies) in three destinations are compared and pitched against the branding of these cities. The companies' names are classified into categories to ascertain whether they reflect (or diverge from) the official strategies. Finally, a conceptual model is developed to explain the findings: the strategic naming model (SNM).

Our main finding is that the overall business features of a place being stronger determinants to the naming strategies than tourist destination branding initiatives. The intrinsic features of a place seem thus to be “above” destination branding policies. The researched features account for different naming strategies, such as highly original names, flat names or non-strategic names.

As the work is based on a convenience sample, it cannot claim strong representativity. The fact that each of the three data sets was processed by a different researcher might bring up personal biases.

This work is a call for a more intensive use of naming strategies to the companies’ advantages, as naming is found out to be strategy used to a very low degree. Thanks to this research, companies will understand the different naming possibilities and be able to apply them to their strategies by choosing names which express “uniqueness” or “belonging”. Practitioners will also be aware of whether they are communicating towards the industry or towards the market.

No works were found that empirically pursue our research goals. Therefore, this research might be considered as a novelty. The proposed SNM model explains and relates the most usual company naming techniques, which were unrelated up to date.