This article aims to present an analysis of the evolution and contributions developed and integrated into the corpus of Earth Jurisprudence from practice in seven (7) South American countries where 135 records were found between 2005 and 2023. The case study was carried out using the methodological approach of the qualitative approach, the hermeneutic method, and the documentary review technique. The unit of analysis was based on the recognition of rights to nature, the data and information organized according to legal/political provisions, the state, the actor that initiated the action, and the ecological actor involved. Among the most outstanding findings, it is evident that a large number of records are concentrated in Ecuador and Colombia. The first correlates with the constitutionalization of the rights of nature and coincides with the second as they have been part of the stream known as new Latin American constitutionalism. In addition, a notable jurisprudential development recognizes nature as a subject of rights and declares it a victim of the armed conflict. Bolivia, which also joined this emerging denomination, has a different tendency than it had in its beginnings, not as the two countries mentioned above have done. Brazil stands out for its considerable increase in such legislative recognition. Argentina has a stronger emphasis on animal law. Peru has an incipient contribution to some regulatory implementation. Finally, Chile, the most laggard, tries it with a new constitution that recognizes these rights without having the approval at the ballot box. It is concluded the need to elevate the rights of nature and animals to constitutional status, claiming indigenous and ancestral cosmogonies regionally since it includes a legal stability that would facilitate the work of judicial and legislative actors and decision-makers for developing public policies, which would contribute to the practical development of the new Latin American constitutionalism and the Earth Jurisprudence.

The aim of this paper is to introduce a research project dedicated to identifying gaps in green skills by using the labor market intelligence. Labor Market Intelligence (LMI). The method is primarily descriptive and conceptual, as the authors of this paper intend to develop a theoretical background and justify the planned research using Natural Language Processing (NLP) techniques. This research highlights the role of LMI as a tool for analysis of the green skills gaps and related imbalances. Due to the growing demand for eco-friendly solutions, there arises a need for the identification of green skills. As societies shift towards eco-friendly economic models, changes lead to emerging skill gaps. This study provides an alternative approach for identification of these gaps based on analysis of online job vacancies and online profiles of job seekers. These gaps are contextualized within roles that businesses find difficult to fill due to a lack of requisite green skills. The idea of skill intelligence is to blend various sources of information in order to overcome the information gap related to the identification of supply side factors, demand side factors and their interactions. The outcomes emphasize the urgency of policy interventions, especially in anticipating roles emerging from the green transition, necessitating educational reforms. As the green movement redefines the economy, proactive strategies to bridge green skill gaps are essential. This research offers a blueprint for policymakers and educators to bolster the workforce in readiness for a sustainable future. This article proposes a solution to the quantitative and qualitative mismatches in the green labor market.

We report on the measurement of the response of Rhodamine 6G (R6G) dye to enhanced local surface plasmon resonance (LSPR) using a plasmonic-active nanostructured thin gold film (PANTF) sensor. This sensor features an active area of approximately ≈ 2.5 × 10¹³ nm² and is immobilized with gold nanourchins (GNU) on a thin gold film substrate (TGFS). The hexane-functionalized TGFS was immobilized with a 90 nm diameter GNU via the strong sulfhydryl group (SH) thiol bond and excited by a 637 nm Raman probe. To collect both Raman and SERS spectra, 10 μL of R6G was used at concentrations of 1 μM (6 × 10¹² molecules) and 10 mM (600 × 10¹⁴ molecules), respectively. FT-NIR showed a higher reflectivity of PANTF than TGFS. SERS was performed three times at three different laser powers for TGFS and PANTF with R6G. Two PANTF substrates were prepared at different GNU incubation times of 10 and 60 min for the purpose of comparison. The code for processing the data was written in Python. The data was filtered using the filtfilt filter from scipy.signals, and baseline corrected using the Improved Asymmetric Least Squares (ISALS) function from the pybaselines.Whittaker library. The results were then normalized using the minmax_scale function from sklearn.preprocessing. Atomic force microscopy (AFM) was used to capture the topography of the substrates. Signals exhibited a stochastic fluctuation in intensity and shape. An average corresponding enhancement factor (EF) of 0.3 × 10⁵ and 0.14 × 10⁵ was determinedforPANTFincubated at 10 and 60 min, respectively.

The technological development and the rise of artificial intelligence are driving a significant transformation of the labor market. The technological unemployment predicted by Keynes poses challenges for the global labor market that require new solutions. Basic income research has become a significant field of study, attracting attention from various disciplines such as political science, law, economics, and sociology. The aim of this paper is to explore on the basis of a literature review, what factors influence the support for basic income among the population. A systematic literature review based on the Web of Science and Scopus databases, after screening 2623 publications, identified 23 articles that contained findings relevant to the research question. A significant number of authors (12/23) analyzed data from the same source, the European Social Survey 2016 (ESS Round 8, 2020), conducted in 2016, first published in 2017 and updated several times since then. The paper shows that the study of the topic has a strong European focus. The social, economic, social and cultural diversity of European countries makes these studies important from a European and EU perspective, but from an international perspective, further research on the topic is needed.

A panel data analysis of nonlinear government expenditure and income inequality dynamics in a macroprudential policy regime was conducted on a panel of 15 emerging countries from 1985–2019, where there had been a non-prudential regime from 1985–1999 and a prudential regime from 2000–2019. The paper explored the validity of the nonlinearity between government expenditure and income inequality in the macroprudential policy regime as well as the threshold level at which excessive spending reduces income inequality using the Bayesian spatial lag panel smooth transition regression (BSPSTR) and fix effect models. The BSPSTR model was adopted due to its ability to address the problems of heterogeneity, endogeneity, and cross-section correlation in a nonlinear framework. Moreover, as the transition variable often varies across time and space, the effect of the independent variables can also be time- and space-varying. The results reveal evidence of a nonlinear effect between government spending and income inequality, where the minimum level of government spending is found to be 29.89 percent of GDP, above which expenditure reduces inequality in emerging countries. The findings confirmed an inverted U-shaped relationship. The focal policy recommendation is that fiscal policy decisions that will reinforce the need for more emphasis on education and public expenditure on education and health, as important tools for improving income inequality, are crucial for these economies. Caution is needed when introducing macroprudential policies, especially at a low level of government expenditure.

Employee retention promotes positivity in an organization and improves employers’ brand value. As the human resource department operates with the objective of improving employees’ contribution towards the organization, meaningful work is an important topic in the core areas of human resource development (HRD), such as employee involvement, motivation, and personal development. Not only salary, benefits, working environment, and status but also the factors that determine whether you enjoy going to work every day are whether you believe that your work makes a meaningful contribution. In HRD, meaningful work comes to the forefront through a connection with a high level of commitment. Thus, this study aims to establish the relationship between meaningful and purposeful jobs affecting employee retention and the mediating factors of person organization fit (POF) and person job fit (PJF). A cross-sectional study involving a survey methodology was used to collect data from 150 white-collar employees working in the IT, banking, textile, and multinational companies in Bangladesh. The results indicate that job meaningfulness has a positive relationship with employee retention (p-value = 0.031) and both the mediating factors of PJF (p-value = 0.040) and POF (p-value = 0.028). The results also indicate that while POF positively influences employee retention (p-value = 0.019), PJF has no significant influence on employee retention (p-value = 0.164). Thus, promoting employee job meaningfulness and purpose in the workplace may represent an opportunity for organizations to improve employee engagement and retention.