Organization For Economic Development Research Articles

A survey of attitudes, behaviors and experiences of Nigerian investors in cryptocurrencies

Purpose Given the many activities of Nigerian investors in the crypto ecosystem, this paper investigates the level of their awareness, attitudes, risk tolerance, experience, reasons for investing and level of financial literacy.Design/methodology/approach The research approach is based on a self-administered questionnaire. The Organization for Economic Cooperation and Development (OECD) permitted the use of its reliable and validated survey instrument, administered in Malaysia, the Philippines and Vietnam in 2019. The results are tabulated and analyzed.Findings The key results include the participation of respondents, who are generally young males, not fully financially literate but risk-averse. Many held the false view that investing in global markets is a higher risk than in national markets. Their reasons for investing in crypto include the fear of missing out on good opportunities and the desire to have fun. The results also revealed that social media, conversations with non-experts and online articles are among the most used investment information sources, highlighting the role of digital platforms and informal discussions in shaping perceptions and knowledge about cryptocurrencies. Investments in cryptos are financed through savings, regular monthly budgets or borrowed from friends or family. As for specific attitudes to risk, the results suggest that for most respondents, preserving their invested capital is of paramount importance.Originality/value The importance of this research also resides in the possibility of comparing the crypto ecosystem in Asia with Nigeria because the same OECD data instrument is employed in data collection. Moreover, this study is the most comprehensive research about Nigerian investors in cryptocurrencies.

Wastewater disinfection with photodynamic treatment and evaluation of its ecotoxicological effects

Research has demonstrated the presence of viruses in wastewater (WW), which can remain viable for a long period, posing potential health risks. Conventional WW treatment methods involving UV light, chlorine and ozone efficiently reduce microbial concentrations, however, they produce hazardous byproducts and microbial resistance that are detrimental to human health and the ecosystem. Hence, there is a need for novel disinfection techniques. Antimicrobial Photodynamic Inactivation (PDI) emerges as a promising strategy, utilizing photosensitizers (PS), light, and dioxygen to inactivate viruses. This study aims to assess the efficacy of PDI by testing methylene blue (MB) and the cationic porphyrin TMPyP as PSs, along a low energy consuming white light source (LED) at an irradiance of 50 mW/cm2, for the inactivation of bacteriophage Phi6. Phi6 serves as an enveloped RNA-viruses surrogate model in WW. PDI experiments were conducted in a buffer solution (PBS) and real WW matrices (filtered and non-filtered). Considering the environmental release of the treated effluents, this research also evaluated the ecotoxicity of the resulting solution (post-PDI treatment effluent) on the model organism Daphnia magna, following the Organisation for Economic Cooperation and Development (OECD) immobilization technical 202 guideline. Daphnids were exposed to WW containing the tested PS at different concentrations and dilutions (accounting for the dilution factor during WW release into receiving waters) over 48 h. The results indicate that PDI with MB efficiently inactivated the model virus in the different aqueous matrices, achieving reductions superior to 8 log10 PFU/mL, after treatments of 5 min in PBS and of ca. 90 min in WW. Daphnids survival increased when subjected to the PDI-treated WW with MB, considering the dilution factor. Overall, the effectiveness of PDI in eliminating viruses in WW, the fading of the toxic effects on daphnids after MB’ irradiation and the rapid dilution effect upon WW release in the environment highlight the possibility of using MB in WW PDI-disinfection.

Analyzing the impact of fiscal conditions on private health expenditures in OECD countries: a quantile ARDL investigation

Organization for Economic Co-operation and Development (OECD) countries have embraced the aim of universal health coverage, as established in Sustainable Development Goal (SDG) 3.8. This goal guarantees access to quality healthcare services without financial hardship or poverty. Additionally, it requires correct and adequate financing sources. A country with weak protection for its population tends to spend less on healthcare and experiences a high share of out-of-pocket payments (OOPs), increasing the likelihood of people falling into poverty. This study aims to understand the relationship and causal effects between macroeconomic and public fiscal conditions and private health expenditure in OECD countries between 1995 and 2019. We retrieved OECD data for 26 OECD countries for the period 1995–2019. Panel AutoRegressive Distributed Lag (PARDL) and panel quantile AutoRegressive Distributed Lag (PQARDL) models were estimated to examine the relationship between private health expenditures and macroeconomic and public fiscal variables. Our results reveal a positive influence of government debt and economic freedom on private health expenditures. They also show a negative influence of the government budget balance, government health expenditures, and economic growth on private health expenditures. These results collectively suggest that public fiscal conditions will likely impact private health expenditures. The findings of this study raise concerns about the equity and financial protection objectives of universal health coverage in OECD countries.

Servicification in Global Value Chains in Emerging and Developing Asian Economies

Servicification in global value chains (GVCs) in emerging and developing Asian economies has become a trend recently. However, there have been no scientific studies to elucidate the mechanism of servicification in GVCs. To fill this gap, this study aims to investigate the involvement of service sectors in GVCs in Asian economies in terms of the quantitative interactions between service inputs and manufacturing exports and inputs and between service inputs and service exports. For this purpose, a panel vector-autoregressive model and the Trade in Value Added database of the Organization for Economic Cooperation and Development (OECD) were used for the empirical analysis during 1995–2018. The estimation results find that, first, there exist reciprocal interactions between the business services and manufacturing sectors; foreign business service inputs are induced by manufacturing exports, whereas manufacturing inputs are induced by business service exports. Second, foreign manufacturing inputs facilitate foreign business service inputs. Third, business service inputs are promoted by business service exports. These trends in the involvement of business services’ involvement in GVCs have accelerated since the mid-2000s. To enhance the role of services in GVCs, Asian economies should facilitate the removal of explicit restrictions in service trade and address regulatory divergence across countries.

Boosting Sinh Cosh Optimizer and arithmetic optimization algorithm for improved prediction of biological activities for indoloquinoline derivatives

Quantitative Structure Activity Relation (QSAR) models are mathematical techniques used to link structural characteristics with biological activities, thus considered a useful tool in drug discovery, hazard evaluation, and identifying potentially lethal molecules. The QSAR regulations are determined by the Organization for Economic Cooperation and Development (OECD). QSAR models are helpful in discovering new drugs and chemicals to treat severe diseases. In order to improve the QSAR model's predictive power for biological activities of naturally occurring indoloquinoline derivatives against different cancer cell lines, a modified machine learning (ML) technique is presented in this paper. The Arithmetic Optimization Algorithm (AOA) operators are used in the suggested model to enhance the performance of the Sinh Cosh Optimizer (SCHO). Moreover, this improvement functions as a feature selection method that eliminates superfluous descriptors. An actual dataset gathered from previously published research is utilized to evaluate the performance of the suggested model. Moreover, a comparison is made between the outcomes of the suggested model and other established methodologies. In terms of pIC50 values for different indoloquinoline derivatives against human MV4-11 (leukemia), human HCT116 (colon cancer), and human A549 (lung cancer) cell lines, the suggested model achieves root mean square error (RMSE) of 0.6822, 0.6787, 0.4411, and 0.4477, respectively. The biological application of indoloquinoline derivatives as possible anticancer medicines is predicted with a high degree of accuracy by the suggested model, as evidenced by these findings.

Comparative Analysis between Quality of Life and Human Labor in Countries Belonging to G7 and BRICS Blocks: Proposition of Discriminant Analysis Model

The aim of the present research is to identify and analyze the variables which help to effectively differentiate Quality of Life (QoL) and human labor in the G7 (Germany, France, Italy, Canada, Japan, United Kingdom, and United States of America—USA) and BRICS countries (Brazil, Russia, India, China, and South Africa) through a discriminant analysis. A discriminant analysis model is developed to classify countries as having a low, mid, or high QoL based on QoL and human labor variables. The variables used in the discriminant analysis were obtained between 2010 and 2022 from two platforms: NUMBEO variables capable of relating QoL to socioeconomic aspects and OECD’s (Organization for Economic Cooperation and Development) human-labor-related variables. Based on the results, the three variables that most discriminate the groups in order of importance are employed women in relation to the female population, the female labor force participation rate, and the female unemployment rate. Countries are classified as having a low, mid, or high QoL. The adopted technique will allow researchers and managers to classify and draw goals for action reorganization and investment in QoL and labor.

The positive relationship between female employment and fertility rates: The role of family benefits expenditure and gender-role ideologies

This article interrogates the impacts of different types of family benefits expenditures on the positive relationship between female employment and fertility rates in developed welfare states. It does this by theorizing how these family benefits align with welfare state regimes’ preferences for different normative gender-role ideologies. Rather than treating family benefits as a monolith, this article investigates the impact of disaggregated expenditures in the Organisation for Economic Co-operation and Development (OECD) family policy database (1. services and in-kind benefits, 2. child-related cash benefits and 3. tax-based financial support for children) on both female employment and fertility rates. This is done using pooled time-series analysis covering the period 2000–9. The analysis yields evidence that expenditure most reflecting a ‘full egalitarian’ gender ideology including service and in-kind benefit provision has the most positive association with female employment and fertility due to an emphasis on defamiliarization. The picture for child-related cash benefits is mixed due to the presence of cash transfer provisions not employment-contingent captured in the indicator. In contrast, tax-based financial support for children harms female employment, reflecting a maternalistic ‘traditional’ ideological orientation, but is positive for fertility rates indicating a moderate pro-natal effect of tax-based financial support for children.

International cross-cultural development and field testing of the primary care practice questionnaire for the PaRIS survey (PaRIS-PCPQ)

BackgroundThe PaRIS survey, an initiative of the Organisation for Economic Co-operation and Development (OECD), aims to assess health systems performance in delivering primary care by measuring the care experiences and outcomes of people over 45 who used primary care services in the past six months. In addition, linked data from primary care practices are collected to analyse how the organisation of primary care practices and their care processes impact care experiences and outcomes. This article describes the development and validation of the primary care practice questionnaire for the PaRIS survey, the PaRIS-PCPQ.MethodThe PaRIS-PCPQ was developed based on domains of primary care practice and professional characteristics included in the PaRIS conceptual framework. Questionnaire development was conducted in four phases: (1) a multi-step consensus-based development of the source questionnaire, (2) translation of the English source questionnaire into 17 languages, (3) cross-national cognitive testing with primary care professionals in participating countries, and (4) cross-national field-testing.Results70 items were selected from 7 existing questionnaires on primary care characteristics, of which 49 were included in a first draft. Feedback from stakeholders resulted in a modified 34-item version (practice profile, care coordination, chronic care management, patient follow-up, and respondent characteristics) designed to be completed online by medical or non-medical staff working in a primary care practice. Cognitive testing led to changes in the source questionnaire as well as to country specific localisations. The resulting 32-item questionnaire was piloted in an online survey and field test. Data from 540 primary care practices from 17 countries were collected and analysed. Final revision resulted in a 34-item questionnaire.ConclusionsThe cross-national development of a primary care practice questionnaire is challenging due to the differences in care delivery systems. Rigorous translation and cognitive testing as well as stakeholder engagement helped to overcome most challenges. The PaRIS-PCPQ will be used to assess how key characteristics of primary care practices relate to the care experiences and outcomes of people living with chronic conditions. As such, policymakers and care providers will be informed about the performance of primary care from the patient’s perspective.

Charting the course: India’s health expenditure projections for 2035

ObjectivesUnderstanding past trends and forecasting future changes in health spending is vital for planning and reducing reliance on out-of-pocket (OOP) expenses. The current study analyzed health expenditure patterns in India and forecasted future trends and patterns until 2035. MethodsData on health expenditure in India from 2000 to 2019 was collected from the Organisation for Economic Co-operation and Development (OECD) iLibrary and National Health Accounts 2019 databases. Gross domestic product (GDP) data from the World Bank was also utilized. Descriptive statistics analyzed the composition and pattern, while the exponential smoothing model forecasted future health expenditures. ResultsThe findings revealed that expenditure made by OOP is the primary health financing source, followed by government and pre-paid private spending. The percentage of GDP allocated to total health expenditure remains stable, while the per capita health expenditure fluctuates. Variations in expenditure among states are observed, with Karnataka relying heavily on pre-paid private coverage. Future projections suggest a decline in per capita and total health expenditure as a share of GDP, with a slight increase in the government’s share. Pre-paid private expenditure per capita and OOP health expenditure as a share of the total is projected to remain relatively constant but still high in absolute terms. ConclusionThe study highlights variations in health spending in India, characterized by high OOP spending, limited public coverage, and a need for investments, and reforms to improve healthcare access and equity.

Evaluation of Neuroprotective effect of Cassia occidentalis L. against Colchicine Induced Memory Impairment in Wistar Rats

Background: Alzheimer’s disease (AD) is a progressive neurological disorder that develops with aging. Objective: In this research, we have examined the anti - Alzheimer’s effect of ethanolic extract from roots of Cassia occidentalis L. on colchicine-induced Alzheimer’s in Wistar rats Methods: Ethanolic extract was obtained and spectroscopic, chromatography analysis was performed. Acute toxicity studies using Organization of Economic Co-operation and Development (OECD) Guidelines 423 were performed to examine and make sure that there were no signs of toxic effects. The induction of AD was done using colchicine which leads to symptoms like neurotoxicity, neuroinflammation, and neurodegeneration. In this experiment, a thorough analysis of body weight, behavioral parameters, locomotor activity, and biochemical evaluation was performed to estimate the medicinal properties of Cassia occidentalis L in treating Alzheimer’s disease. Results: Pharmacognostic analysis showed the presence of vascular bundles, starch grains, fibers, calcium oxalate crystals, elongated parenchyma, and collenchyma mucilage as shown in the supplementary files. Locomotor activity, Escape latency time, Conditioned avoidance response, and Transfer latency were improved with treatment. Interleukin- 6 (IL - 6) levels were reduced significantly in the Colchicine + 200 Cassia mg/kg group (739.2 ± 0.37 pg/ml) than in the Colchicine Group (850.6±0.40 pg/ml). Tumor necrosis factor (TNF-α) was decreased in the Colchicine + 200 Cassia mg/kg Group (1030.93±0.51 pg/ml) than in the Colchicine Group (1455.06±1.25 pg/ml). A significant decrease in total protein level was observed in the Colchicine Group (2.52±0.10 mg/ml), (3.33±0.90 mg/ml) as compared to Colchicine + 200 Cassia mg/kg Group (5.27±0.09 mg/ml, (5.01±0.10 mg/ml) respectively, in the Hippocampus and Entorhinal cortex. The levels of antioxidant enzymes such as Catalase (CAT), Serum superoxide dismutase (SOD), Reduced glutathione (GSH) and Malondialdehyde (MDA) were measured. When compared to the Colchicine Group (7.33±0.16 nM/ mg, the MDA level was lower in the Colchicine + 100 Cassia mg/kg Group (3.20±0.01 nM/ mg). The level of CAT in Colchicine + 200 Cassia mg/kg Group (7.01±0.03 μmoles of H2O2/mg of protein) was seen to be increased when compared to Colchicine Group (3.32 ± 0.17 μmoles of H2O2/mg of protein). The level of SOD in Colchicine + 200 Cassia mg/kg Group (7.43±0.02 U mg -1 of protein) was seen to be increased when compared with Colchicine Group (4.55±0.03 U mg -1 of protein). The level of GSH in Colchicine + 200 Cassia mg/kg Group (10.07±0.19 nM/mg -1 of protein) was increased when compared with the Colchicine Group (5.82±0.11nM/mg -1 of protein). Histopathology of the Hippocampus and Entorhinal cortex showed diminished amyloid plaques, and neurodegeneration in the treatment groups Conclusion: The present study showed that ethanolic extract from the roots of Cassia occidentalis L. At 100 and 200 mg/kg doses in Wistar rats improved memory damage, by reducing oxidative stress. Levels of the antioxidant enzymes as CAT, and SOD, GSH were increased and MDA was decreased. The cytokine levels in the serum of Wistar rats of IL-6 level and TNF-α level were reduced significantly. Estimation of total protein level was found to be increased. It restored neuronal degeneration in the Hippocampus, and Entorhinal cortex and reduced oxidative stress. This suggests that the ethanolic extract of Cassia occidentalis L. could be an effective therapeutic treatment for neurodegenerative diseases like AD.

How natural resource, renewable energy, and energy productivity integrate with environmental quality under the load capacity curve in OECD nations

Previous research highlights the impact of renewable energy (REN) sources and natural resources (NRP) on environmental sustainability, but it leaves out the possible consequences of energy production (EP). Additionally, clean environment is addressed by Sustainable Development Goals 7 and 12. This study evaluates the outcomes of meeting the OECD's carbon zero targets by 2050 as well as the UN Climate Change Conference of the Parties' 2030 carbon neutrality target. Therefore, evaluating how these factors affect the load capacity factor (LCF) may have pertinent ramifications for the government's pursuit of sustainable development objectives. Therefore, the effects of REN, NRP, and energy efficiency on LCF were examined for Organization for Economic Cooperation and Development (OECD) countries. The method of momentum quantile regression (MMQR) is applied during the period of 1990–2022. The results show that REN is increasing LCF by 0.157%–0.161% in four quantiles and NRP is also contributing to environmental quality by 0.385%–0.233% in 25th to 90th quantiles. EP is lowering LCF by 0.091%–0.073% in the long run. The paper provides policy implications for a cleaner environment in OECD nations.

The Impact of Social Work Relationships on Preschool Teachers' Social and Emotional Competence

In recent years, the Organization for Economic Co-operation and Development (OECD) initiated a survey focused on the social and emotional competence (SEC) of educators, garnering significant attention across the educational community. Despite this interest, there remains a notable gap in research concerning the development of SEC among preschool teachers within the context of various social relationships. Addressing this gap, our study examines the influence of leadership trust, collegial relationships, pro-teacher relationships, teacher-child interactions, and self-efficacy on the SEC of preschool educators. This investigation aims to elucidate the role these social relationships play in shaping the SEC of preschool teachers. The study sample consisted of 223 Chinese preschool teachers, with data analyzed through hierarchical regression techniques. Findings reveal that leadership trust, pro-teacher relationships, and self-efficacy are significant predictors of teachers' SEC. These results underscore the importance of fostering a positive, trust-based, and supportive social work environment as a pivotal strategy for enhancing preschool teachers' SEC, thereby contributing to the broader understanding of how social relationships influence educators' emotional and social capabilities.

Development of a Robust Read-Across Model for the Prediction of Biological Potency of Novel Peroxisome Proliferator-Activated Receptor Delta Agonists.

A robust predictive model was developed using 136 novel peroxisome proliferator-activated receptor delta (PPARδ) agonists, a distinct subtype of lipid-activated transcription factors of the nuclear receptor superfamily that regulate target genes by binding to characteristic sequences of DNA bases. The model employs various structural descriptors and docking calculations and provides predictions of the biological activity of PPARδ agonists, following the criteria of the Organization for Economic Co-operation and Development (OECD) for the development and validation of quantitative structure-activity relationship (QSAR) models. Specifically focused on small molecules, the model facilitates the identification of highly potent and selective PPARδ agonists and offers a read-across concept by providing the chemical neighbours of the compound under study. The model development process was conducted on Isalos Analytics Software (v. 0.1.17) which provides an intuitive environment for machine-learning applications. The final model was released as a user-friendly web tool and can be accessed through the Enalos Cloud platform's graphical user interface (GUI).

A web GIS based integrated water resources assessment tool for Javeh Reservoir

The creation of tools and services for tracking, estimating, and predicting water resource indices that might provide authorities access to information in close to real-time is essentially a must. The considerable development of Web-Geographic Information System Decision Support System (Web-GIS DSS) allows for the analysis of geospatial data and scenarios via the internet without a traditional desktop GIS. The web GIS technology is coupled to techniques which determine water resources Carlson, and Organization for Economic Corporation and Development (OECD) Trophic Status Indices (TSIs), the water resource vulnerability index (WRVI), and social water stress index (SWSI). The water quality indices were determined by helping machine learning (ML) techniques, Decision Tree, Random Forest, and XGBoost. The performances of aforementioned MLs were compared, and the best efficient one, XGBoost, was included in the Web-GIS DSS tool. The developed Web-GIS DSS was examined in Javeh Reservoir, Kurdestan, Iran.The developed Web-GIS DSS allows the users to define the relevant features of the Javeh Reservoir system in pre-defined time horizons such as meteorological, hydrological, inflow water quality, reservoir operation strategies, downstream water demands, geographical external water transfers, etc. The results indicate that the Javeh Reservoir experiences eutrophication status according to the Carlson and OECD indices over time horizons. The water quantity assessment reveals the Javeh Reservoir's susceptibility based on WRVI, although no stress is indicated by SWSI. This susceptibility may be attributed to limited precipitation and water inflow during the simulation period, suggesting a need for comprehensive water resources management.The conclusion drawn from this research underscores the essential role of the developed Web-GIS DSS in decision-making processes for water and environment management, substantiating its practicality with accurate and user-friendly water and environmental data analysis. The tool exemplifies the potential of integrating ML and Web-GIS technologies to promote sustainable environmental practices, thereby establishing a model for future research and policy-making initiatives.

An ethical foundation of global competence and its educational implications

ABSTRACT This paper proposes an ethical foundation of global competence and highlights its educational implications by critiquing the conception promoted by the Organisation for Economic and Co-operation and Development (OECD). It is contended that OECD’s formulation of global competence presupposes neo-liberal ideas and pays insufficient attention to ethical concerns, especially those originating from the Global South. Drawing upon Confucian thought, it is argued that Confucius predicates global competence upon an ethical way of being that revolves around who we are and how we are connected to others in the world. The normative basis of global competence are ren (humanity) and shu (empathy) that advance the collective good of all human beings. As for educational implications, Confucian perspectives foreground the dispositional and moral aspects of global competence, as well as the importance of social justice education. Such a construct guides and motivates globally competent individuals to balance critical thinking and empathic concern.

Measuring the gap between optimal and observed energy structure: Evidence from 36 OECD countries

Sustainable development has always been given priority by economic authorities, therefore pursuing both environmental emissions reduction and economic growth at the same time is required. However, energy structure is often disregarded in existing performance evaluation methodologies, despite its essential function in determining environmental efficiency or productivity. This study shows how ignoring the energy structure can lead to distorted policy recommendations as well as evaluation results. The present study provides a non-parametric estimating approach to quantify the difference between the optimal (theoretical) energy structure required to achieve sustainable development and the actual (observed) energy structure. This method may assess the energy transition process and evaluate the observed and optimal energy structure of a country or region. We demonstrate that using the countries of the Organization for Economic Co-operation and Development as an example, that only a limited number of countries are able to meet their objectives for carbon reduction and economic development simultaneously without transforming their energy structure. The relationship between energy structure and green total factor productivity (GTFP) was further studied using a two-stage least squares regression on the observed energy structure and GTFP. The findings indicate that most countries need to increase their share of renewable energy in order to achieve green growth.

A systematic literature review to explore the antecedents of employee engagement among remote workers

PurposeThis study aims to identify and review research articles to understand the conceptualization of employee engagement (EE) in a remote working environment. Specifically, the aim is to explore the antecedents impacting remote workers’ engagement.Design/methodology/approachA systematic literature review was conducted, encompassing empirical studies sourced from EBSCO, Emerald and Gale databases. Studies published in peer-reviewed journals between 2013 and 2023 covering countries in the Organization for Economic Co-operation and Development (OECD) were included. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed to capture the review process.FindingsA total of 25 empirical studies published across 18 journals were synthesized, with the results being reported in terms of three research objectives. The researchers identified that individual, organizational/job resources and organizational/job demands are the three main antecedents affecting EE in remote working environments.Research limitations/implicationsThis study can serve as an important source of information for academics and practitioners as well as postulate new avenues for the future research. While the Job Demands-Resources model remains relevant in specifying demands and resources as antecedents of workforce engagement, technological antecedents gain prominence as additional factors contribute to the engagement of remote workforce.Originality/valueThis article studies the shifting landscape of EE with the rise of remote working and the need to gain a better understanding of how to keep remote workers engaged.

Analysis of the relationship between carbon pricing and green innovation: A multidimensional study in 35 countries

Increased greenhouse gas emissions are the main cause of global warming, leading to effects such as rising sea levels, extreme weather events, and unprecedented species extinction. The 2015 Paris Agreement, with the participation of 195 countries, aimed to reduce CO₂e emissions and limit the increase in global temperature to 2 °C compared to pre-industrial levels. Academia, the World Bank, and the Organization for Economic Co-operation and Development emphasize CO₂e pricing as a crucial initiative to mitigate global warming and promote a low-carbon economy. This can be achieved through taxes on fossil fuel emissions or a carbon credit auction system such as the Emissions Trading System (ETS). However, complexity arises when considering cross-border pricing limitations and the concern that companies may relocate to countries with less stringent environmental regulations. Therefore, the objective of this study is to investigate the correlations between the 35 countries that have CO₂e pricing practices. Data and methods involved statistical analysis of three exogenous variables using SPSS software: a) countries' position in the Environmental Performance Index (EPI) ranking; b) historical number of green patents registered in these countries; and c) the number of scientific articles published with decarbonization as a central topic. The results suggest a virtuous cycle in these countries, where CO₂e pricing leads to an increase in green articles and patents, contributing to their improved position in the global EPI ranking. The main implications of this study are that achieving the objectives of the Paris Agreement will require a collective effort from all countries, and therefore, good practices must be encouraged and replicated. Meeting decarbonization targets necessitates structural changes, such as those in the current energy model. This virtuous cycle should be extended to other countries that do not yet practice CO₂e pricing to advance the goal of mitigating global warming and transitioning to a low-carbon economy.

Quantitative read-across structure-activity relationship (q-RASAR): A novel approach to estimate the subchronic oral safety (NOAEL) of diverse organic chemicals in rats

We have developed a quantitative safety prediction model for subchronic repeated doses of diverse organic chemicals on rats using the novel quantitative read-across structure-activity relationship (q-RASAR) approach, which uses similarity-based descriptors for predictive model generation. The experimental -Log (NOAEL) values have been used here as a potential indicator of oral subchronic safety on rats as it determines the maximum dose level for which no observed adverse effects of chemicals are found. A total of 186 data points of diverse organic chemicals have been used for the model generation using structural and physicochemical (0D–2D) descriptors. The read-across-derived similarity, error, and concordance measures (RASAR descriptors) have been extracted from the preliminary 0D–2D descriptors. Then, the combined pool of RASAR and the identified 0D–2D descriptors of the training set were employed to develop the final models by using the partial least squares (PLS) algorithm. The developed PLS model was rigorously validated by various internal and external validation metrics as suggested by the Organization for Economic Co-operation and Development (OECD). The final q-RASAR model is proven to be statistically sound, robust and externally predictive (R2 = 0.85, Q2LOO = 0.82 and Q2F1 = 0.94), superseding the internal as well as external predictivity of the corresponding quantitative structure-activity relationship (QSAR) model as well as previously reported subchronic repeated dose toxicity model found in the literature. In a nutshell, the q-RASAR is an effective approach that has the potential to be used as a good alternative way to improve external predictivity, interpretability, and transferability for subchronic oral safety prediction as well as ecotoxicity risk identification.

The OECD’s narrative on the future curriculum: issuing values

ABSTRACT This paper explores the work of a particular document in issuing educational values. The document is the report Embedding Values and Attitudes in Curriculum: Shaping a Better Future, launched in 2021 and published by the Organisation for Economic Co-operation and Development (OECD). Inspired by a practice-oriented method of document analysis and the concepts of modifying work and contexting, we show how the issue of values is modified and transformed through the text. We illustrate how different data is used in the transformation with examples from the Nordic countries. Our analysis revealed five modifications that transformed the issue of values from a global societal issue embedded in international and national regulations to an issue defined by the OECD’s Learning Compass and its nine competencies. The report gives prominence to the individual learner and competencies needed to navigate towards a future of well-being. Hence, the issue of values is reduced to universal competencies, and the report can manoeuvrer its argument to avoid issuing values as something controversial. Finally, we argue that the ways in which values are issued implies a curriculum design that is not compatible with the traditional curriculum format based on didaktik and Nordic ambitions.