Green dreams are made of this: Futures consciousness and proenvironmental engagement.

Futures consciousness (FC) refers to the capacity to understand, anticipate and prepare for the future. As a form of future orientation, it encompasses five interrelated dimensions of time perspective, agency beliefs, openness to alternatives, systems perception and concern for others. We present here cross-sectional evidence that FC is related to greater environmental engagement, above and beyond other future orientation constructs. In two pre-registered studies (one convenience student sample and one representative sample; N = 1041), we found that respondents with higher futures consciousness reported greater proenvironmental behaviour (consumption behaviour, land stewardship, social environmentalism and environmental citizenship). FC proved a better predictor of proenvironmental behaviour than the Zimbardo Inventory's Future Time Perspective and the Consideration for Future Consequences Scale (Study 1). FC was also related to stronger biospheric values (Study 2). However, it was not significantly related to personal environmental footprint (derived from a 16-item calculator). Strikingly, the environmental footprint was also unrelated to the Proenvironmental Behaviour Scale, which could point to a lack of correspondence between measures of proenvironmental propensity and impact. We discuss implications for future-thinking research and interventions aiming to improve futures consciousness.

Industry visions of technology for older adults: A futures anthropology perspective.

The negative portrayal of ageing as a human decline burdening society has prompted Ageing Technology industries (AgeTech) to foresee solutions rooted in the Ageing in Place paradigm. These ostensibly neutral future interventions are intertwined with socio-technical dynamics. While Science and Technology Studies (STS) and anthropology scholars have questioned these AgeTech practices, limited literature explores industry's predictions of future AgeTech. Drawing on STS and futures-anthropology literature, I interrogate AgeTech industry visions of future assemblages involving older people, smart home technology, and socio-material discourses rooted in their own discrepancies and dilemmas. To unpack AgeTech futures, my methods include a review of 49 industry reports and 29 interviews with industry experts. Based on the reports, I designed comics to be used in interviews with experts spanning CEOs and managers of companies designing technology for older people, consultants, and aged-care workers based in 12 countries. Ageing futures are far from being neutral or a chronological process, instead they are non-consensual and fragmented. In the review and interviews, I captured future assemblages of a fragmented AgeTech industry in relationships with governments and industry giants. The fragmentation continues unfolding in participants from diverse countries and professions contesting dominant AgeTech narratives. In dissecting future assemblages, I also unpack non-consensual futures based on diverging experts' values (e.g. safety versus activity) and humans' values like control and improvisation challenging predictive and surveillance technology. AgeTech Futures transcend physical matters or assemblages of technologies and humans. They encompass future normativities, tensions, divergent values, and ideological concepts. I propose not only alternatives to the visions found in industry narratives, but also encourage scholars to understand the AgeTech industry's dilemmas.

Care Literacy for Culture, Nature, and Future.

Within the broader sustainability agenda, an important element relates to the need for a transformative approach to nature. This motivates and is reflected in the Natures Futures Framework. Within this framework, this letter focuses on the relational value of Nature as Culture/One with Nature. This is important yet complex as part of the re-orienting of values to enable truly significant change, and which necessitates individual and community involvement on the value of caring for nature. As a means for understanding and enabling individuals' potential to engage and contribute, the notion of 'care for nature literacy' is put forward.

RV-FELM: Futures commodity price forecasting based on RIME-VMD algorithm coupled with FA-ELM.

Commodity futures are an important hedging tool in material trade, and by accurately predicting prices, countries and firms are able to make informed production and consumption decisions. This paper introduces a novel machine learning ensemble method that combines decomposition algorithms and physical optimization algorithms to predict commodity futures prices. First, the VMD(Variational mode decomposition) is optimized by the RIME algorithm (Rime optimization algorithm) to obtain the optimal modal decomposition results, and the trend and seasonal terms are predicted using the ELM (Extreme Learning Machines) and FA (Fourier Attention) models, respectively, and the results are finally synthesized. The results show that the MAPE(mean absolute percentage error) of one-step, three-step, and six-step methods for predicting crude oil prices are 0.48%, 0.66%, and 0.75%, respectively, and the MAPE of soybean prediction results are 0.22%, 0.27%, and 0.37%, respectively. The empirical results and ablation experiments show that it outperforms other benchmark models in terms of both horizontal and directional accuracy. Notably, it outperforms in predicting soybean futures prices, which demonstrates the ability of our model to better capture the characteristics of both the time and frequency domains of the series, to take sufficient consideration of the series characteristics, and to ensure robustness.

Infection prevention and control in 2030: a first qualitative survey by the Crystal Ball Initiative.

BACKGROUND: Healthcare delivery is undergoing radical changes that influence effective infection prevention and control (IPC). Futures research (short: Futures), the science of deliberating on multiple potential future states, is increasingly employed in many core societal fields. Futures might also be helpful in IPC to facilitate current education and organisational decisions. Hence, we conducted an initial survey as part of the IPC Crystal Ball Initiative. METHODS: In 2019, international IPC experts were invited to answer a 10-item online questionnaire, including demographics, housekeeping, and open-ended core questions (Q) on the "status of IPC in 2030" (Q1), "people in charge of IPC" (Q2), "necessary skills in IPC" (Q3), and "burning research questions" (Q4). The four core questions were submitted to a three-step inductive and deductive qualitative content analysis. A subsequent cross-case matrix produced overarching leitmotifs. Q1 statements were additionally coded for sentiment analysis (positive, neutral, or negative). RESULTS: Overall, 18 of 44 (41%) invited experts responded (from 11 countries; 12 physicians, four nurses, one manager, one microbiologist; all of them in senior positions). The emerging leitmotifs were "System integration", "Beyond the hospital", "Behaviour change and implementation", "Automation and digitalisation", and "Anticipated scientific progress and innovation". The statements reflected an optimistic outlook in 66% of all codes of Q1. CONCLUSIONS: The first exercise of the IPC Crystal Ball Initiative reflected an optimistic outlook on IPC in 2030, and participants envisioned leveraging technological and medical progress to increase IPC effectiveness, freeing IPC personnel from administrative tasks to be more present at the point of care and increasing IPC integration and expansion through the application of a broad range of skills. Enhancing participant immersion in future Crystal Ball Initiative exercises through simulation would likely further increase the authenticity and comprehensiveness of the envisioned futures.

Centering the geographical imaginations of research participants in narrating speculative futures.

In this commentary, I consider how geographers narrating speculative futures might risk disempowering their research participants. Reflecting on my work with community cultural organizations, I discuss the importance of centering participants and their geographical imaginations of their own futures in qualitative research projects. I then consider restructuring researcher-participant voice in the narration of speculative futures, and my use of future-focused questioning.

What Do Community Doulas Think About the Future of the Doula Workforce?

INTRODUCTION: Expanding access to doula care is a key strategy for improving the perinatal experiences and health outcomes of birthing people of color in the U.S. This study investigates the future of maternal healthcare in the U.S. from the perspective of doulas and highlights emerging technology and other opportunities related to strengthening the doula workforce. METHODS: The study recruited community doulas from 12 unique U.S. states, ensuring at least half of the doulas predominantly served communities of color. Doulas (N = 26) participated in semi-structured, futures-oriented interviews that explored their experiences providing care during the COVID-19 pandemic and utilization of technology. A subset of doulas (n = 8) were engaged in interactive workshops where they envisioned alternative futures for doula care and childbirth. Interviews and workshops were analyzed using the Framework Method. RESULTS: The COVID-19 pandemic heightened technology use among doulas and increased client accessibility. Social media serves as a unique space for critical community building and client outreach. Doulas reported opportunities to strengthen and mobilize the future workforce: recognizing doula care as a reimbursable service by health insurers, utilizing doula collectives for community practice to decrease burnout, increasing emotional support for doulas, and instilling a chain of learning through mentorship. DISCUSSION: Futures thinking served as a valuable approach for doulas to illuminate the implications of present-day challenges and empowered doulas to design roadmaps toward better futures for doulas and maternal health. Doulas should be engaged as partners to hold a meaningful decision-making role when discussing policies, employment structures, emerging technology, and other aspects of doulas' positioning within the healthcare system.

Supporting human factors and ergonomics professionals in anticipating future work changes in response to the anthropocene.

Ergonomics is evolving towards including a broader consideration of ecological and political factors in the design of work environments by adopting an interconnected systems paradigm, highlighting the importance of considering the ecological and political impacts of business. The emergence of 'green ergonomics' encourages sustainable human systems integrated in their natural environment, while respecting ethical values such as respect for human rights and diversity. On the one hand, this is leading to new areas of ergonomic research and intervention, such as energy management and corporate CSR, and on the other, to the need to develop specific skills to anticipate the future in innovative ways. For Human Factors and Ergonomics professionals (HF&E professionals), this means adopting prospective approaches that incorporate tools and methods to promote foresight, as well as creativity to imagine potential future work activities.

Equilibrium bifurcation and extreme risk in the EU carbon futures market.

Considering the long-term memory and volatility clustering of the European Union (EU) Carbon Emission Allowances (EUA) futures returns, based on the economy-energy-environment system perspective and the assumption of investors' heterogeneity, this study proposes a joint modeling approach combining the fractionally integrated generalized autoregressive conditional heteroscedasticity model (FIGARCH) and the stochastic cusp catastrophe model (SCC) to examine the equilibrium bifurcations and extreme risks in the EU carbon futures market. The relevant results are threefold. (1) The SCC model has good fitting effect and interpretability, and is an effective method for investigating catastrophe reactions under time-varying volatility conditions. (2) In the EUA futures market, chartists are mainly affected by short-term price and trading volume changes, which leads to the emergence of equilibrium bifurcations, while fundamentalists make investment decisions based on the economy, the energy market, and market supply-demand, which affects the asymmetry of equilibrium bifurcations. (3) Using the catastrophe criterion (i.e., Cardan's discriminant of the equilibrium surface equation), we identify148 equilibrium bifurcation time points in the EUA futures market from December 3, 2009 to September 16, 2020, most of which are concentrated in two upward periods with an average scale of extreme risks is about 32.51 %. Our analysis provides theoretical support for regulatory authorities to stabilize the carbon futures market and build a collaborative extreme risk management framework covering energy and macroeconomics, also proposing suggestions for traders to effectively prevent extreme risks.

Ocean warming and acidification adjust inter- and intra-specific variability in the functional trait expression of polar invertebrates.

Climate change is known to affect the distribution and composition of species, but concomitant alterations to functionally important aspects of behaviour and species-environment relations are poorly constrained. Here, we examine the ecosystem ramifications of changes in sediment-dwelling invertebrate bioturbation behaviour-a key process mediating nutrient cycling-associated with near-future environmental conditions (+ 1.5 °C, 550 ppm [pCO2]) for species from polar regions experiencing rapid rates of climate change. We find that responses to warming and acidification vary between species and lead to a reduction in intra-specific variability in behavioural trait expression that adjusts the magnitude and direction of nutrient concentrations. Our analyses also indicate that species behaviour is not predetermined, but can be dependent on local variations in environmental history that set population capacities for phenotypic plasticity. We provide evidence that certain, but subtle, aspects of inter- and intra-specific variation in behavioural trait expression, rather than the presence or proportional representation of species per se, is an important and under-appreciated determinant of benthic biogeochemical responses to climate change. Such changes in species behaviour may act as an early warning for impending ecological transitions associated with progressive climate forcing.

NPCC4: Concepts and tools for envisioning New York City's futures.

This chapter of the New York City Panel on Climate Change 4 (NPCC4) report discusses the many intersecting social, ecological, and technological-infrastructure dimensions of New York City (NYC) and their interactions that are critical to address in order to transition to and secure a climate-adapted future for all New Yorkers. The authors provide an assessment of current approaches to "future visioning and scenarios" across community and city-level initiatives and examine diverse dimensions of the NYC urban system to reduce risk and vulnerability and enable a future-adapted NYC. Methods for the integration of community and stakeholder ideas about what would make NYC thrive with scientific and technical information on the possibilities presented by different policies and actions are discussed. This chapter synthesizes the state of knowledge on how different communities of scholarship or practice envision futures and provides brief descriptions of the social-demographic and housing, transportation, energy, nature-based, and health futures and many other subsystems of the complex system of NYC that will all interact to determine NYC futures.

Machine learning-based surrogate modelling of a robust, sustainable development goal (SDG)-compliant land-use future for Australia at high spatial resolution.

We developed a high-resolution machine learning based surrogate model to identify a robust land-use future for Australia which meets multiple UN Sustainable Development Goals. We compared machine learning models with different architectures to pick the best performing model considering the data type, accuracy metrics, ability to handle uncertainty and computational overhead requirement. The surrogate model, called ML-LUTO Spatial, was trained on the Land-Use Trade-Offs (version 1.0) model of Australian agricultural land system sustainability. Using the surrogate model, we generated projections of land-use futures at 1.1 km resolution with 95% classification accuracy, and which far surpassed the computational benchmarks of the original model. This efficiency enabled the generation of numerous SDG-compliant (SDGs 2, 6, 7, 13, 15) future land-use maps on a standard laptop, a task previously dependent upon high-performance computing clusters. Combining these projections, we derived a single, robust land-use future and quantified the uncertainty. Our findings indicate that while agricultural land-use remains dominant in all Australian regions, extensive carbon plantings were identified in Queensland and environmental plantings played a role across the study area, reflecting a growing urgency for offsetting greenhouse gas emissions and the restoration of ecosystems to support biodiversity across Australia to meet the 2050 Sustainable Development Goals.

SF-Transformer: A Mutual Information-Enhanced Transformer Model with Spot-Forward Parity for Forecasting Long-Term Chinese Stock Index Futures Prices.

The complexity in stock index futures markets, influenced by the intricate interplay of human behavior, is characterized as nonlinearity and dynamism, contributing to significant uncertainty in long-term price forecasting. While machine learning models have demonstrated their efficacy in stock price forecasting, they rely solely on historical price data, which, given the inherent volatility and dynamic nature of financial markets, are insufficient to address the complexity and uncertainty in long-term forecasting due to the limited connection between historical and forecasting prices. This paper introduces a pioneering approach that integrates financial theory with advanced deep learning methods to enhance predictive accuracy and risk management in China's stock index futures market. The SF-Transformer model, combining spot-forward parity and the Transformer model, is proposed to improve forecasting accuracy across short and long-term horizons. Formulated upon the arbitrage-free futures pricing model, the spot-forward parity model offers variables such as stock index price, risk-free rate, and stock index dividend yield for forecasting. Our insight is that the mutual information generated by these variables has the potential to significantly reduce uncertainty in long-term forecasting. A case study on predicting major stock index futures prices in China demonstrates the superiority of the SF-Transformer model over models based on LSTM, MLP, and the stock index futures arbitrage-free pricing model, covering both short and long-term forecasting up to 28 days. Unlike existing machine learning models, the Transformer processes entire time series concurrently, leveraging its attention mechanism to discern intricate dependencies and capture long-range relationships, thereby offering a holistic understanding of time series data. An enhancement of mutual information is observed after introducing spot-forward parity in the forecasting. The variation of mutual information and ablation study results highlights the significant contributions of spot-forward parity, particularly to the long-term forecasting. Overall, these findings highlight the SF-Transformer model's efficacy in leveraging spot-forward parity for reducing uncertainty and advancing robust and comprehensive approaches in long-term stock index futures price forecasting.

Dynamic spillover between crude oil, gold, and Chinese stock market sectors -analysis of spillovers during financial crisis data during the last two decades.

The present study investigates the presence of asymmetric return spillovers among crude oil futures, gold futures, and ten Chinese stock sector markets. Time-varying asymmetric spillovers between commodities and the 10 sectors are shown by utilizing the spillover index developed by Diebold and Yilmaz (2012, 2014). Our findings indicate that the industrial and discretionary consumer sectors generate and benefit the most from spillovers. Furthermore, it has been established that the basic materials sector exhibits a net positive impact on spillovers. In contrast, oil futures, gold futures, and other sectors demonstrate a net negative impact as recipients of spillovers. Moreover, the negative return spillovers outweigh the positive return spillovers. Our analysis spans from 2000 to 2023 to include various financial crises. The spillover effects of asymmetry are impacted by various factors, including the global financial crisis (GFC), the European sovereign debt crisis (ESDC), the decline in oil prices, and the outbreak of the COVID-19 pandemic. Including gold and oil in individual equity markets can benefit equity investors. Furthermore, implementing hedging strategies is susceptible to the global financial crisis, economic slowdown, oil price decline, and the recent COVID-19 pandemic. The oil futures exhibit the greatest hedging effectiveness during the COVID-19 spread. The findings indicate that gold exhibits comparable outcomes solely in the presence of positive spillover effects. At the same time, its performance reaches its peak during the recovery phase in the context of negative spillover effects.

Identifying dynamic risk spillovers between crude oil and downstream industries: China's futures market perspective.

Interactions between crude oil and its downstream products are crucial but complex. The main purpose of this study is to examine the risk spillover relationships between the crude oil futures market and the petrochemical downstream futures market in the context of the COVID-19 epidemic in China. By combining the dynamic conditional correlation-generalized autoregressive conditional heteroskedasticity (DCC-GARCH) model and the Diebold-Yilmaz spillover index based on time-varying parameter-vector autoregression (TVP-VAR-DY), we investigate the dynamic correlations between Shanghai crude oil futures (INE) and the downstream futures in China's petrochemical industry chain. At the same time, we also incorporate the representative global crude oil futures (BRENT and WTI) in our study as a comparative analysis. Our results show a significant positive correlation between three crude oil futures and China's downstream future products, with a more pronounced link observed between INE and the downstream futures market. Moreover, the correlation between crude oil futures and various downstream products exhibits heterogeneity; that is, direct derivatives of crude oil show higher sensitivity to price fluctuations compared to products with longer production chains. Furthermore, the spillover results indicate that the international crude oil futures, particularly BRENT, primarily function as spillover transmitters, while INE mainly serves as the recipient. In the post-pandemic period, the international crude oil market still exhibits a high spillover effect, and the spillover effect of INE to polyvinyl chloride, pure terephthalic acid, and bitumen futures increased, reflecting market recovery in China to some extent. These results provide potential insights for policymakers, financial institutions, industry participants, and investors, emphasizing the importance of enhanced risk management, diversified investment strategies, and attention to market dynamics.

Exploring the driving forces and scenario analysis for catastrophic and impoverishing health expenditures in Iran.

BACKGROUND: The extent of healthcare expenditure within households stands as a crucial indicator in low and middle-income countries (LMICs). When out-of-pocket healthcare expenses surpass household income or become unduly burdensome, it serves as a significant socio-economic alarm, resulting in a reduced quality of life, a phenomenon referred to as 'catastrophic health expenditure (CHE).' Multiple factors can contribute to the occurrence of CHE. The study's objective was to identify the key uncertainties and driving forces influencing CHE to develop scenarios in Iran on the horizon of 2030. METHODS: This study was conducted between December 2021 and January 2023, data were collected through a literature review, and experts' opinions were gathered via questionnaires, interviews, and expert panels. The statistical population included experts in the fields of health policy, health economics, and futures studies. Scenario Wizard software and MICMAC analysis were employed for data analysis, providing valuable insights into potential future scenarios of health expenditures in Iran. RESULTS: Based on the results of the scoping review and semi-structured interview, 65 key factors in the fields of economics, politics, technology, social, and environmental were identified. The findings of the MICMAC analysis presented 10 key variables. Finally, six main scenario spaces are depicted using Scenario Wizard. These scenarios included catastrophic cost crises, sanction relief, selective information access, technological ambiguity, induced demand management, and incremental reforms. CONCLUSIONS: Each of the six drawn scenarios provides images of the future of health expenditure in Iranian households on the horizon of 2030. The worst-case scenario from all scenarios was scenario one, with the most probable and critical features to derive Iran's health expenditures. The current study is a valuable addition to the literature depicting the key drivers that all developing nations can consider to decrease exposing households to catastrophic and impoverishing health expenditures.

Advancing policy design through creative engagement with lived experience: the Tomorrow Party.

We consider how lived experience might actively inform policy design. Good policy design calls for analysis of problems, how they might be addressed, and likely outcomes. Policy scholars and practitioners have devised methods that bring rigor to policy design through problem framing, assessment of potential interventions, and prediction of outcomes of those interventions. This pursuit of analytical and predictive rigor has often given short shrift to the insights of people whose lives are affected by current challenges and who will be impacted by policy change. Our theory of change is that creative engagement with citizens can generate insights of high value to the process of policy design. We introduce the Tomorrow Party - a design method for generating novel stakeholder insights regarding desirable future states. We then discuss initial findings from a series of pilots. Those findings suggest the Tomorrow Party is a broadly applicable creative tool for advancing policy design.

Anticipation in the biosciences and the human right to science.

Anticipation entails contemplating the beneficial and harmful impacts of scientific and technological progress. Anticipation has a long history in science, technology, and innovation policy partly due to future impacts of scientific progress being inescapable. The link between anticipation, an undertheorized concept, and human rights law is yet to be fully explored. This paper links anticipation to the rights to science, a lesser-studied human right codified in the International Covenant on Economic, Social, and Cultural Rights. The paper argues that the normative content of the right includes anticipation entitlements and duties. Combining the entitlements and duties with anticipation typologies leads to identifying three forms of anticipation that governments (and, in some cases, scientists) must carry out: beneficial, responsible, and participatory anticipation. The paper concludes by identifying three ways in which further conceptual work can enrich human-rights-based anticipation.

The impact of index futures crash risk on bitcoin futures returns and volatility.

This study examines the relationship between E-mini S&P 500 futures' crash risk and Bitcoin futures' returns and volatility using data from 2017 to 2021. While E-mini S&P 500's crash risk doesn't significantly influence Bitcoin returns, it correlates with its volatility, especially during events like the COVID-19 pandemic and U.S. elections. Furthermore, as global and emerging market indices rise, Bitcoin futures volatility decreases, suggesting its role as a hedging tool. These findings are pivotal for investors aiming to construct informed trading strategies, leverage Bitcoin futures as a hedging asset during economic instability, and keep tabs on traditional market indicators like E-mini S&P 500 crash risk for anticipating fluctuations in Bitcoin futures.

Price discovery in Chinese PVC futures and spot markets: Impacts of COVID-19 and benchmark analysis.

Despite being a minor futures category, Polyvinyl chloride (PVC) futures have emerging as a vital element in energy and chemical futures domain. Employing three benchmark models component share (CS), information share (IS), and information leadership share (ILS), this study explores the price discovery function of Chinese PVC futures and spot markets. It assesses whether PVC futures have matured into an effective hedging tool and reference point for spot markets, and also examines the impact of the COVID-19 pandemic on this price discovery relationship. Empirical analysis reveals that the futures market has become the primary site for price discovery in the Chinese PVC market. All the models consistently demonstrate a mature price discovery function in PVC futures, providing risk mitigation tools for industry players. However, post-pandemic dynamics indicate that price discovery in PVC markets primarily occurs within the spot market. This suggests that compared to the futures market, the PVC spot market is able to respond more quickly to the strong signals of industrial recovery after the end of the pandemic. The feedback and pricing efficiency of the PVC futures market in response to new market information are also influenced. Furthermore, our study offers better anticipation of future market prices.