CDD, or Contamination Detection via output Distribution, identifies data contamination by measuring the peakedness of a model's sampled outputs. We study the conditions under which this approach succeeds and fails on small language models ranging from 70M to 410M parameters. Using controlled contamination experiments on GSM8K, HumanEval, and MATH, we find that CDD's effectiveness depends critically on whether fine-tuning produces verbatim memorization. In the majority of conditions we test, CDD performs at chance level even when the data is verifiably contaminated and detectable by simpler methods. We show that probability-based methods, specifically perplexity and Min-k\% Prob, outperform CDD in all conditions where any method exceeds chance, suggesting that CDD's peakedness-based approach is insufficient for contamination detection in small language models. Our code is available at https://github.com/Sela-Omer/Contamination-Detection-Small-LM
Dynamic capabilities are widely recognized as a catalyst for firm performance yet there is a dearth of research on how dynamic capabilities work with human and substantive capabilities to contribute to firm performance particularly in women-owned micro and small firms. This study investigates the influence of human capabilities on firm performance, mediated by both substantive and dynamic capabilities. Drawing on Zahra et al., (2006) conceptual model of substantive and dynamic capabilities, we test the relationship between human capabilities of women business owners and substantive and dynamic capabilities as they act on firm performance. We find that human capabilities directly and indirectly influence firm financial performance, mediated by substantive and dynamic capabilities. Substantive capabilities do not directly influence firm performance but have a role indirectly through dynamic capabilities. The results illuminate the interplay between capabilities as key drivers of financial performance and contribute novel insights into human and substantive and dynamic capabilities for policymakers when developing policy to support micro and small firm performance.
Small and medium-sized businesses, artisans, handicrafts, trades, Business
This paper conceptualizes the Canadian music industry as an entrepreneurial ecosystem, applying an ecosystem lens to a creative sector where artists act as entrepreneurs. By examining systemic conditions such as finance, networks, leadership, talent, knowledge, and intermediary services, it highlights how cultural, economic, and institutional forces interact to generate innovation and value. At the same time, benefits are unevenly distributed: women, Black professionals, and other equity-deserving groups face persistent barriers to mentorship, leadership, and professional services. The music industry therefore illustrates both the potential and the paradox of entrepreneurial ecosystems. It raises a central question: how can an entrepreneurial ecosystem be considered productive when systemic exclusion prevents full participation?
Arts in general, Small and medium-sized businesses, artisans, handicrafts, trades
In today’s environment, the search for ways to bring small and medium-sized businesses and higher education closer together in order to achieve national development goals is a topic of scientific debate and discussion. Approaches to assessing such interaction have been considered, in which various sets of indicators and metrics have been proposed, but they do not cover the entire area of responsibility that currently lies with business and higher education. To justify the need to create conditions for small and medium-sized businesses and hig her education interaction, a wide range of data has been analyzed using correlation-regression analysis and machine learning methods. The results obtained made it possible to cluster variables from the presented data set in order to identify their interrelationships, including through the impact of common factors, as well as to cluster regions depen ding on the identified interrelated variables. The exploratory model built on the data obtained confirms the hypothesis about the need to search for those indicators of the studied systems that influence each other and social and economic development in general. At the same time, the set of such indicators varies for each regional cluster.
Businesses heavily rely on data sourced from various channels like news articles, financial reports, and consumer reviews to drive their operations, enabling informed decision-making and identifying opportunities. However, traditional manual methods for data extraction are often time-consuming and resource-intensive, prompting the adoption of digital transformation initiatives to enhance efficiency. Yet, concerns persist regarding the sustainability of such initiatives and their alignment with the United Nations (UN)'s Sustainable Development Goals (SDGs). This research aims to explore the integration of Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG) as a sustainable solution for Information Extraction (IE) and processing. The research methodology involves reviewing existing solutions for business decision-making, noting that many systems require training new machine learning models, which are resource-intensive and have significant environmental impacts. Instead, we propose a sustainable business solution using pre-existing LLMs that can work with diverse datasets. We link domain-specific datasets to tailor LLMs to company needs and employ a Multi-Agent architecture to divide tasks such as information retrieval, enrichment, and classification among specialized agents. This approach optimizes the extraction process and improves overall efficiency. Through the utilization of these technologies, businesses can optimize resource utilization, improve decision-making processes, and contribute to sustainable development goals, thereby fostering environmental responsibility within the corporate sector.
Trades are important objects in combinatorial design theory that may be realized as certain elements of kernels of inclusion matrices. Total trades were introduced recently by Ghorbani, Kamali and Khosravshahi, who showed that over a field of characteristic zero the vector space of trades decomposes into a direct sum of spaces of total trades. In this paper, we show that the vector space spanned by the permutations of a total trade is an irreducible representation of the symmetric group. As a corollary, the previous decomposition theorem is recovered. Also, a basis is obtained for the module of total trades in the spirit of Specht polynomials. More generally, in the second part of the paper we consider intersection matrices and determine the irreducible decompositions of their images. This generalizes previously known results concerning ranks of special cases.
Fantasy football leagues involve strategic player trades to optimize team performance. However, identifying optimal trades is complex due to varying player projections, positional needs, and league-specific scoring. Existing approaches focus on team selection or lineup optimization, but automated trade generation remains underexplored. In this paper, an algorithm that generates optimal trades, biasing toward improved playoff performance while maintaining apparent fairness for negotiation is explored. We introduce a genetic algorithm for fantasy football trade optimization, building on existing frameworks for team selection and lineup generation. The algorithm initializes with single-player trades, evolves through custom mutations (add/remove players, combine trades, exchange players, add from other trades, and spawn new trades), and uses team-specific elitism to preserve diversity. The cost function incorporates a playoff-weighted gain for the user's team (while maintaining apparent fairness), opponent gain, and fairness penalty. Integration with ESPN data sources enables real-time projections for all positions, including kickers and defenses. On a 12-team ESPN league (Week 8, 2025), the algorithm generated trades that upgraded the projected point totals of both the trade initiator and trade partner by nearly 3 fantasy points per week ensuring positive gains for both teams. The algorithm demonstrates effective trade optimization, with potential extensions to other fantasy sports or combinatorial problems requiring temporal biasing. Open-source implementation enables practical use and further research.
The relevance of the research topic is due to significant changes in business conditions and the need to assess their impact on the activities of small and medium-sized enterprises. At the current stage of the geo-economic confrontation, the domestic economy is faced with large-scale restrictions and measures to curb its development. Solving the problem of the emerging shortage of financial and other resources involves their optimal distribution between business entities and their groups, including between small and large businesses. The priority recipients of resources should be groups of systemically important entities capable of ensuring the sustainability and dynamic development of the entire economy. In the article, the author considers the question of whether domestic small and medium-sized enterprises belong to such entities. The purpose of the study is to assess the role and potential of small and medium-sized businesses in ensuring sustainable and dynamic development of the domestic economy in modern conditions. The author presents the results of systematization of current scientific approaches on the topic under consideration, indicators characterizing the share of small and medium-sized businesses in the economy of Russia and a number of foreign countries. A criteria analysis of its role and potential in ensuring the development of the domestic economy has been performed. The prerequisites for changing this role in the medium term are assessed. To achieve the goal of the article, the results of Russian and foreign research, statistical observation data, as well as methods of criterial and comparative analysis were used. When studying the prerequisites for increasing the role of small and medium-sized businesses, a factorial method was used based on a set of factors presented by the author. The results of the study confirmed the special importance of small and medium-sized businesses for ensuring the social aspects of economic development, including ensuring employment and stimulating private initiative. It is concluded that there is a need to increase government support in this area. In the broader context of economic development, domestic small and medium-sized businesses are characterized as a relatively small part of the national economy with a moderate level of stability in times of crisis and relatively low innovative activity and susceptibility to innovation. Its influence on economic growth is assessed as limited, and its role in ensuring sustainable and dynamic development of the domestic economy is assessed as secondary and complementary. There are no prerequisites for a significant change in this role in the medium term, which is due to the existing economic structure, industry structure and modern business conditions. The results of scientific research may be in demand by experts in the field of strategic socio-economic planning.
Entrepreneurship promotes economic growth, particularly in developing economies where small and medium-sized enterprises (SMEs) are a significant source of employment and economic activity. However, SMEs in developing countries often face various resource constraints and weak institutions, forcing them to engage in entrepreneurial bricolage behavior by creatively combining existing resources. This study explores the relationship between entrepreneurial bricolage and product, process, and marketing innovation among SMEs in the Philippines. Logistic regression estimates reveal that entrepreneurial bricolage has a significant and positive impact on product, process, and marketing innovation. As entrepreneurial bricolage behavior increases, so does the probability of innovation, highlighting the importance of creative problem-solving in settings with inadequate resources. The study also emphasizes the need for policies that support SMEs by providing enabling resources, such as robust infrastructure and reliable communication platforms, to encourage firm innovation that fosters positive spill-over effects on the broader economy.
Small and medium-sized businesses, artisans, handicrafts, trades, Business
In modern conditions caused by the instability of the national economy, the role of small and medium-sized businesses (SMEs) in the country's economy is increasing many times. Insurance is a reliable tool for protecting entrepreneurs from risks and ensuring the sustainability of their business. The purpose of this article is to study the current problems and prospects for the development of SME insurance in the context of external economic sanctions and market volatility. The object of the study is the SME insurance system in Russia. Scientific work contributes to the theory of insurance, in particular, to substantiate the need for insurance in the development of entrepreneurship and its role for the country's economy. The results of the study can be used to develop measures of state support for SME insurance, as well as to improve insurance products aimed at entrepreneurs.
Chest X-ray is a commonly used tool during triage, diagnosis and management of respiratory diseases. In resource-constricted settings, optimizing this resource can lead to valuable cost savings for the health care system and the patients as well as to and improvement in consult time. We used prospectively-collected data from 137 patients referred for chest X-ray at the Christian Medical Center and Hospital (CMCH) in Purnia, Bihar, India. Each patient provided at least five coughs while awaiting radiography. Collected cough sounds were analyzed using acoustic AI methods. Cross-validation was done on temporal and spectral features on the cough sounds of each patient. Features were summarized using standard statistical approaches. Three models were developed, tested and compared in their capacity to predict an abnormal result in the chest X-ray. All three methods yielded models that could discriminate to some extent between normal and abnormal with the logistic regression performing best with an area under the receiver operating characteristic curves ranging from 0.7 to 0.78. Despite limitations and its relatively small sample size, this study shows that AI-enabled algorithms can use cough sounds to predict which individuals presenting for chest radiographic examination will have a normal or abnormal results. These results call for expanding this research given the potential optimization of limited health care resources in low- and middle-income countries.
Reza Khanmohammadi, Simerjot Kaur, Charese H. Smiley
et al.
This paper investigates the relationship between scientific innovation in biomedical sciences and its impact on industrial activities, focusing on how the historical impact and content of scientific papers influenced future funding and innovation grant application content for small businesses. The research incorporates bibliometric analyses along with SBIR (Small Business Innovation Research) data to yield a holistic view of the science-industry interface. By evaluating the influence of scientific innovation on industry across 10,873 biomedical topics and taking into account their taxonomic relationships, we present an in-depth exploration of science-industry interactions where we quantify the temporal effects and impact latency of scientific advancements on industrial activities, spanning from 2010 to 2021. Our findings indicate that scientific progress substantially influenced industrial innovation funding and the direction of industrial innovation activities. Approximately 76% and 73% of topics showed a correlation and Granger-causality between scientific interest in papers and future funding allocations to relevant small businesses. Moreover, around 74% of topics demonstrated an association between the semantic content of scientific abstracts and future grant applications. Overall, the work contributes to a more nuanced and comprehensive understanding of the science-industry interface, opening avenues for more strategic resource allocation and policy developments aimed at fostering innovation.
For more than 25 years, the Instituto Argentino de Radioastronomía has been directing efforts from basic research and radio astronomy development to technology transfer projects around Argentina's National Space Plan and to Small and Medium Enterprises. With the surge of COVID-19, our organization's transformation accelerated, bringing new opportunities and challenges which can be applied to impact health, education, processes and businesses. In this article, we explore our efforts to bridge the gap between basic science and the needs of our society.
Purpose – While research has identified a consistent link between startup intent and entrepreneurship education (EE) intentions, studies also indicate that many entrepreneurs lack the EE they need. However, research examining factors that explain why certain individuals with high startup intent pursue EE while others do not is rare. Given this, the purpose of this paper is to examine how individual characteristics moderate the startup intent EE intentions relationship. Design/methodology/approach – Survey data were gathered on 199 US adults. Moderators examined include attitudes toward education, perceived entrepreneurial efficacy, propensity for risk taking and the Big Five personality traits. Linear regression models were used to test each of the moderation relationships predicted. Findings – Notable findings suggest that extroversion, openness to experience, agreeableness, perceived entrepreneurial efficacy and risk propensity reduce the chances that individuals with high startup intent will pursue EE, while viewing education as instrumental enhances the relationship. Research limitations/implications – Study findings imply that EE programs might not be reaching critical target markets, suggest that EE programs might need to be modified to attract individuals with high startup intent and indicate that individual characteristics are key factors that determine why certain individuals with high startup intent pursue EE while others with the same desires do not pursue EE. Originality/value – This study builds on previous work that looks at the relationship between startup intent and EE intentions by investigating how individual characteristics either amplify or diminish the relationship, increasing scholarly knowledge about why certain individuals with high startup intent pursue EE while others do not.
Small and medium-sized businesses, artisans, handicrafts, trades, Business
Any firm whose business strategy has an exposure constraint that limits its potential gain naturally considers expansion, as this can increase its exposure. We model business expansion as an enlargement of the opportunity set for business policies. However, expansion is irreversible and has an opportunity cost attached. We use the expected optimization of utility to formulate this as a novel stochastic control problem combined with an optimal stopping time, and we derive an explicit solution for exponential utility. We apply the framework to an investment and a reinsurance scenario. In the investment problem, the cost and incentives to increase the trading exposure are analyzed, while the optimal timing for an insurer to launch its reinsurance business is investigated in the reinsurance problem. Our model predicts that the additional income gained through business expansion is the key incentive for a decision to expand. Interestingly, companies may have this incentive but are likely to wait for a period of time before expanding, although situations of zero opportunity cost or specific restrictive conditions on the model parameters are exceptions to waiting. The business policy remains on the boundary of the opportunity set before expansion during the waiting period. The length of the waiting period is related to the opportunity cost, return, and risk of the expanded business.
All of the known circumbinary planets are large (> 3 Earth radii). Whilst observational biases may account for this dearth of small planets, in this paper we propose a theoretical explanation. Most of the known planets are near the stability limit, interspersed between potentially unstable 5 : 1, 6 : 1 and 7 : 1 mean motion resonances with the binary. It is believed that these planets did not form in situ, but rather migrated from farther out in the disc, and hence passed through these resonances. Planets are expected to migrate at a speed proportional to their mass, and a slower rate makes resonant capture and subsequent ejection more likely. Therefore, whilst large planets may be able to successfully "run the gauntlet", small planets may be imperiled. This hypothesis is tested using N-body integrations of migration in a truncated and turbulent disc. We discover that surprisingly none of the known planets exist interior to a fully unstable resonance. We demonstrate that resonant ejection of migrating planets may occur in nature, and that it does indeed disproportionately affect small planets, but it requires a highly turbulent disc and its efficiency is likely too low to fully explain a dearth of < 3 Earth radii planets.
Carlos Bazan, Hannah Gaultois, Arifusalam Shaikh
et al.
Purpose – The study aims to test the applicability of a variant of the model proposed by Hockerts (2017) for assessing the social entrepreneurial intention (SEI) of male and female students. It extends the model by incorporating the university's environment and support system (ESS) as an additional more distal construct. The university's ESS, coupled with the experience with social, cultural and environmental issues can affect SEI by influencing the more proximal precursors of empathy towards others, perceived self-efficacy, perceived community support and social, cultural and environmental responsibility. Design/methodology/approach – A structured non-disguised questionnaire was administered to students at a Canadian university. A sample of 485 usable responses was analysed by means of second-order structural equation modelling. Findings – The results provide confirmation that the proposed model is a multi-group invariant and appropriate for analysing the SEI of male and female students. They also show that the university's ESS helps predict SEI indirectly through the complete mediation of the more proximal antecedents. Research limitations/implications – The questionnaire is limited to universities with social innovation and entrepreneurship initiatives. Practical implications – Outcomes of the study can help universities assess the efficacy of their social innovation and entrepreneurship initiatives for instilling a social entrepreneurial mind-set in students. Consequently, universities will be better equipped to raise the perceptions of venture feasibility and desirability, thus increasing students' perceptions of opportunity. Originality/value – The study advances the social entrepreneurial knowledge of the university's effect on the precursors of SEI.
Small and medium-sized businesses, artisans, handicrafts, trades, Business
This study aims to systematically review the key characteristics and issues in Corporate Social Responsibility among Small and Medium Enterprises (CSRS) research. The Systematic Assessment Quantitative Technique (SQAT) developed by Australian researchers, Catherine Pickering and Jason Antony Byrne, was used to identify and analyse 62 peer-reviewed CSRS articles from six high quality academic databases. Most of the studies took place in Europe and Asia while South America has been largely ignored. A significant number of CSRS research were empirical in nature, meaning that there is a need for more conceptual studies to aid the understanding of new CSRS norms and underlying factors. Additionally, CSRS articles focused mainly on identifying the various ways SMEs are implementing CSR. Finally, most CSRS articles adopted a single research method, with survey being the most dominant method. There is a need for future studies to combine a variety of methods so as to gain additional insight into CSRS related issues
Small and medium-sized businesses, artisans, handicrafts, trades, Business