Multiple Causality Research Articles

Green transformation paths of resource-based cities in China from the configuration perspective

Green transformation is an unavoidable choice for resource-based cities (RBCs) that face resource depletion and environmental pollution. Existing research has focused primarily on specific RBCs, making it challenging to apply green transformation strategies universally across cities. The fuzzy set qualitative comparative analysis (fsQCA) is a combination of qualitative and quantitative analyses that can handle multiple concurrent causality problems and determine how different conditions combine into configurations and generate an outcome. Thus, to address this gap, in this study, we established a research framework for green transformation and utilized the fsQCA to examine the configurations of 113 RBCs in China. By incorporating the element of time, this study explored the dynamic evolution of solutions in 2013, 2016, and 2019. The main findings indicate that individual elements do not constitute the necessary conditions for improving the green transformation efficiency (GTE), and the systematic combination of multiple conditions is an effective path for realizing the improvement of the GTE in RBCs. Green transformation paths of RBCs exhibit the same destination through different paths. Additionally, the combination of system environment elements and system structure elements is both complementary and alternative. Differences in RBCs have led to various factor combinations and development paths, but there are some similarities in the key elements of the factor combinations at different stages. Economic environment, government support, and technological innovation are key factors that universally enhance the GTE in RBCs. These insights can assist city managers in formulating policies to drive green transformation and contribute to a better theoretical understanding of green transformation paths in RBCs.

Association between depressive symptoms and cardiovascular diseases in the Korean geriatric population: A nationwide retrospective cohort study

IntroductionDepression has emerged as a modifiable risk factor for cardiovascular disease (CVD). However, evidence on whether depressive symptoms measured using a self-report questionnaire are associated with CVD incidence is scarce. Therefore, we aimed to investigate the association between depressive symptoms and CVD risk using data from national health examinations and insurance claim records. MethodsThis retrospective cohort study included participants who underwent the Korean National Screening Program for Transitional Ages at age 66 years between 2007 and 2017. The presence of depressive symptoms was defined as affirmative responses to any of three questions (loss of activities and interests, worthlessness, and hopelessness) selected from the Geriatric Depression Scale. Incident composite CVD event included myocardial infarction, stroke, heart failure, and CVD death. The association between depressive symptoms and CVD risk was evaluated using hazard ratios (HRs) and 95 % confidence intervals (CIs) estimated with Cox proportional hazards models. ResultsAmong 88,765 participants (48.5 % women) aged 66 years, 4036 incident CVD events occurred during a mean follow-up of 6.8 years. Participants with depressive symptoms had a significantly higher risk of CVD than those without depressive symptoms (adjusted HR = 1.16 [95 % CI: 1.07–1.24]). The three individual depressive symptoms showed similar associations with CVD risk (loss of activities and interests, adjusted HR = 1.17 [95 % CI: 1.08–1.26]; worthlessness, 1.15 [1.03–1.29]; hopelessness, 1.13 [1.01–1.26]). LimitationsThe study was limited to participants aged 66 years. Despite extensive adjustment for potential confounders and multiple sensitivity analyses, residual confounding and reverse causality could not be ruled out. ConclusionThe presence of depressive symptoms was associated with an increased risk of CVD. Screening for depressive symptoms in the general population may effectively mitigate the burden of CVD.

Using fs/QCA to explore the influencing factors of urban green infrastructure development and its combinational drivers: the case of the Yangtze River Delta region of China.

High levels of urban green infrastructure (UGI) development can help mitigate the climate, biodiversity, and habitat crises faced by cities and support the achievement of sustainable urban development. Based on the relevant data of 41 cities in the Yangtze River Delta region obtained from 2011 to 2020, this study measured the development level of natural and geographic conditions, economic development, urban construction, social and cultural development, and eco-environment quality and urban green infrastructure (UGI); evaluated the development trend of UGI in the region during the 12th Five-Year Plan and 13th Five-Year Plan by using entropy TOPSIS; and used fs/QCA to explain the high-level development path of each city toward the achievement of a green infrastructure. The results showed that (1) the development level of UGI in the Yangtze River Delta region decreases from southeast to northwest, and gradually decreases from Shanghai, Hangzhou, and other central cities. (2) There were several different configurations of high levels and non-high levels of UGI development drivers across regions, confirming the existence of multiple causality and asymmetry indices in the drivers of UGI. (3) During the "12th Five-Year Plan" and the "13th Five-Year Plan" period, the conditions needed to achieve a high level of UGI gradually became stricter, expanding from nature-social culture and urban construction-eco-environmental drivers to nature-urban construction, nature-social culture-eco-environmental, urban construction-economy-social culture-eco-environmental drivers. Research findings can provide greater guidance and implications for future sustainable urban development.

Investigating the impact of 'dark nudges' on drinking intentions: A between groups, randomized and online experimental study.

This study explored how 'dark nudges' (tactics used in alcohol industry-funded responsible drinking campaigns) affect drinking intentions, perceived source credibility and whether individual differences in perceptions of prototypical drinkers moderated these effects. Two 2 × 2 between-groups online experimental studies. Study 1 (N = 164) presented three alcohol health messages per condition, comprising social norm (healthy/unhealthy ("dark nudge")) by frame (loss/gain). Study 2 (N = 229) presented one message per condition, comprising cancer causality (single cause/multiple causes (dark nudge)) by funding disclosure (disclosure/non-disclosure (dark nudge)). Outcomes were drinking intentions and perceived source credibility. Exploratory analyses considered prototype perceptions as a between-subjects moderator. No significant effects of message frame, social norm, fundi or multiple cancer causality arguments on drinking intentions were found. In Study 2, in the dark nudge multiple cancer causality conditions, perceived source credibility was high when funding was undisclosed, but significantly lower when it was disclosed. Exploratory analyses suggested effects were moderated by prototype similarity. In Study 1, higher perceived similarity to a heavy drinker and lower perceived similarity to a responsible drinker were associated with higher drinking intentions in the unhealthy norm/gain frame condition, but lower drinking intentions in the other conditions. Framing, social norm, funding disclosure and multiple causality manipulations as tested in this study did not exert a dark nudge effect on drinking intentions. However, the exploratory analyses suggest it could be hypothesised that the types of messages used in alcohol industry-funded responsible drinking campaigns may result in greater drinking intentions among those who identify more as heavy drinkers and less as responsible drinkers. Perceived prototype similarity may be an important moderator of the impact of alcohol health messages that warrants further research. Study 2 suggests disclosure of industry funding guides judgements of the credibility of sources of misleading messages about alcohol and cancer.

The Influence of Cryptocurrency (Bitcoin), IHSG, Fed Rate, and BI Rate on IDX BUMN 20 Stock Prices

The cryptocurrency market has grown significantly in recent years, with Bitcoin emerging as the dominant player. This research aims to investigate the relationship between cryptocurrency (Bitcoin) prices, the Indonesia Stock Exchange Composite Index (IHSG), the Federal Reserve (Fed) Rate, and the Bank Indonesia (BI) Rate with the stock prices of IDX BUMN20 companies. The study adopts a quantitative research approach, utilizing historical time-series data for the variables of interest spanning a specific period. The data will be collected from reputable financial databases and sources. Multiple regression analysis and White analysis causality tests will be employed to examine the potential influence of these factors on IDX BUMN20 stock prices. The findings from this research are expected to shed light on the interconnectedness of the cryptocurrency market with the traditional stock market in Indonesia and provide valuable insights for investors, policymakers, and market participants. Understanding these relationships can aid in risk management strategies and investment decision-making. However, it is crucial to note that the cryptocurrency market is known for its volatility and speculative nature, which may introduce unique challenges in interpreting the results. Therefore, cautious consideration and expert financial advice.

Multi-scenario prediction and path optimization of industrial carbon unlocking in China

China's industry is facing a carbon lock-in (CLI) dilemma. Based on the complexity and dynamics of CLI, exploring diversified unlocking paths is an important way to achieve emission reduction goals. This paper innovatively applies system dynamics (SD) to the study of CLI prediction and unlocking path, and systematically constructs an industrial CLI SD model, trying to break the positive feedback mechanism of CLI through multiple causality and feedback chains. This paper simulates and predicts the changing trend of the CLI level of China's industry and 8 major subsectors from 2020 to 2050. At the same time, the random forest algorithm is used to select the regulatory variables of policy analysis. Compared with the previous research methods, the accuracy and objectivity of the selection of regulatory variables are improved, so as to test the effectiveness of the unlocking path under each scenario. The results show that (1) the whole industry faces a serious CLI problem and is still in a deep lock-in state. From the perspective of subsectors, the light, electromechanical, and textile industries have achieved unlocking; the oil and extractive industries are in a moderately lock-in state; the chemical, steel, and power industries are in a deep lock-in state; and the CLI situation is serious. (2) The results of the random forest algorithm show that R&D investment, the proportion of fixed asset investments in the energy industry, car sales, energy structure, and carbon emission industry structure are the most significant factors affecting CLI in each subsystem. (3) Compared with the existing economic development model, the technological, institutional, social, and comprehensive unlocking scenarios can all enable industry to achieve carbon peak and carbon unlocking in advance. However, the effect of each scenario is as follows: comprehensive unlocking scenario > technological unlocking scenario > institutional unlocking scenario > social unlocking scenario. (4) The unlocking times of the oil, chemical, steel, and power industries are relatively late in each scenario. To realize carbon unlocking in industry, these four areas should be focused on in the future. This study helps policymakers formulate reasonable policies to accelerate industrial carbon unlocking and promote the implementation of the “dual carbon” strategy.

Research on agricultural technology gap between China and Africa and its optimization path: based on meta-frontier SBM and fsQCA

Recently, COVID-19 pandemic, locust plague, drought and conflict have seriously affected the development of agriculture in Africa, which make Africa countries difficultly to achieve the Sustainable Development Goals (SDGs) 1 and 2. As the cornerstone of agricultural development, technological progress has made brilliant contributions to achieving food security and nutrition improvement in African countries. And as the largest economic and trade partner of Africa, analyzing the agricultural technology gap between China and African countries and exploring optimal paths also has great significance for achieving SDGs 8 and 9. Therefore, the paper used the Meta-frontier SBM model to measure the agricultural technology gap between China and African countries from 2003 to 2019, and explores sources of the gap. On this basis, 24 African countries were taken as samples to identify multiple paths for narrowing the technology gap between China and Africa with the help of the configuration analysis method of the fuzzy-set qualitative comparative analysis (fsQCA). The results showed that the overall agricultural technology gap between China and Africa was narrowing, which was mainly caused by the reduction of pure technical inefficiency. However, sources of technology gap in African countries with different economic development levels were different. Configuration analysis found that agricultural technology innovation and institutional environment were the key conditional variables to narrow the agricultural technology gap between China and Africa. Five paths had been formed around two key conditional variables, and further summarized into three driving modes: “technology-environment” driving mode, “technology-organization” driving mode and “organization-environment” driving mode. Furthermore, this paper explored the multiple concurrent causality of narrowing the technology gap, which overcomes the deficiency of using regression methods. The paper highlights the importance of enhancing the integration of technical, organizational, and environmental conditions in African countries to collectively advance agricultural scientific and technological progress

Growth of Venture Firms under State Capitalism with Chinese Characteristics: Qualitative Comparative Analysis of Fuzzy Set

This study builds upon the venture growth literature and venture legitimation mechanisms and investigates how venture firms in China can acquire legitimacy and necessary resources from state stakeholders for venture growth during the COVID-19 pandemic. To offer a context-specific perspective of Chinese ventures’ legitimation strategies, we discuss that under Chinese state capitalism, these ventures need to follow lingering socialist values, such as equality and social stability, to be recognized as appropriate business operations by state audiences. Furthermore, we discuss that access to necessary resources for venture growth is limited during crises. Based on the understanding of particular contexts of Chinese state capitalism and the COVID-19 pandemic, we examine how various sets of a venture’s identity, associative, and organizational mechanisms influence venture growth during crises in China. In addition, we consider serial entrepreneurship as a contextual factor affecting the effectiveness of causal effects. This study applies the fuzzy-set qualitative comparative analysis method to take a configurational approach and identify multiple concurrent causality of legitimacy mechanisms on venture growth. We conduct a survey and analyze data from 107 entrepreneurs of Chinese technology ventures during the COVID-19 pandemic. Findings show that Chinese ventures with or without repeat entrepreneurs can actively utilize various sets of legitimation mechanisms to acquire legitimacy and necessary resources from Chinese state audiences for venture growth during adversity. This study provides comprehensive understanding and practical implications on Chinese ventures’ legitimation strategies for venture growth during crises.

Construction of Frugal Innovation Path in the Context of Digital Transformation: A Study Based on NCA and QCA

With the continuous advancement of digital globalization, enterprises need to seek development opportunities in the context of diversification and resource shortage. Frugal innovation provides a new way for enterprises to realize social value and create a win-win situation. Based on 113 enterprises’ survey data, fuzzy set qualitative comparative analysis (fsQCA) and necessary condition analysis (NCA) are used to explore the multiple concurrency factors and causality mechanisms of digital transformation, organizational resilience, learning from failure and design thinking for frugal innovation. It is found that: (1) Digital transformation, organizational resilience, internal learning from failure, external learning from failure and design thinking cannot effectively stimulate frugal innovation alone, and linkage matching of multiple antecedents is needed to promote frugal innovation. (2) There are three paths to producing high frugal innovation, namely, external learning from failure and design thinking driving under digital transformation learning from failure driving under design thinking guidance, organizational resilience driving under digital transformation. (3) There are two paths to produce non-high frugal innovation, which are asymmetrical with high frugal innovation path. Our results are helpful for the study of digital transformation and frugal innovation at the enterprise level. In addition, our research results also provide practical solutions and a theoretical basis for enterprises to carry out frugal innovation activities under the new economic normal.

An Action Research to Improve Change and Continuity Perception in Social Studies

The purpose of this study is to develop the students’ skills of change and continuity through activities based on the objects in fourth-grade social studies. In alignment with the scope, an action research design was used in which the researcher is also the executor. A criterion sampling was used for recruitment which resulted in 17 fourth-grade students agreeing to participate in the study. Data collection tools included achievement test, open-ended questions, semi-structured interview forms, video recording and student journals. Wilcoxon signed ranks test, grading key and content analysis were used in the analysis of the data. The results of the study showed that there is a significant difference between the pre-test and post-test scores of students in object-based activities. Within the scope of change and continuity, it was seen that students can identify similarities and differences, make estimations on the perception of future time, discover the effects of sociocultural context along with change and continuity, provide chronological visual evidences, and put them in order. However, it was found that students can’t develop multiple causality relationships related to change, that they interpret causes in relation to change and continuity from a limited perspective, that they do not consider different disciplines when expressing the powerful effects of technology in change processes.

Causal complexity of environmental pollution in China: a province-level fuzzy-set qualitative comparative analysis.

Environmental problems are endowed with the causal complexity of multiple factors. Traditional quantitative research on the influencing mechanism of environmental pollution has tended to focus on the marginal effects of specific influencing factors but generally neglected the multiple interaction effects between factors (especially three or more). Based on the panel data of 30 Chinese provinces between 2011 and 2020, this study employs fuzzy set qualitative comparative analysis (fsQCA) - which can provide a fine-grained insight into the causal complexity of environmental issues - to shed light on the influencing mechanism of environmental pollution. The results show that there are several different configurations of pollution drivers which lead to high pollution or low pollution in provinces, confirming the multiple causality, causal asymmetry, and equifinality of environmental pollution. Furthermore, the combination effect of advanced industrial structure, small population size, and technological advance is significant in achieving a state of green environment compared to environmental regulation factors. In addition, spatiotemporal analysis of the configurations indicates that strong path dependencies and spatial agglomeration exist in current local environmental governance patterns. Finally, according to our findings, targeted policy recommendations are provided.

Social stability risk assessment and economic competitiveness in China

Social stability risk assessment (SSRA) has become the mainstream policy instrument for assessing potential risks of large-scale development projects across all sectors in China. In this paper, fuzzy qualitative comparative analysis (fsQCA) is used to quantify the impact of SSRA policy on economic competitiveness across China’s 31 provinces using a SSRA policy dataset (2003–2020) and a provincial economic competitiveness dataset (2019–2020). QCA combines Boolean algebra and set theory to identify configurations of conditions that are necessary or sufficient for a given outcome. Rather than following the mainstream statistical method of developing a single causal model that best fits the data, QCA explores multiple concurrent causality. A typology of SSRA policies was developed to guide our analysis. The research concluded that to support high economic competitiveness within provinces, SSRA policies must be structured around solving social stability problems and addressing a specific industry issue (e.g., pollution) in a particular industry (e.g., resources). Policies that only include one of these factors or that focus on the performance of government officials were found to contribute to low economic competitiveness. Reorienting the focus of SSRA policies could support more rigorous risk assessments and enhance economic competitiveness, particularly in provinces that host large-scale development projects. These findings have implications for China’s policymakers given their dual objectives of driving economic reform while maintaining a harmonious society.

Threats to Democracy

After a discussion of the literature on the development of societies and of the multiple causality of societies, this paper discusses 12 threats to democracy: autocracy, cultural decline, polarisation, elite paradox, populism, confusion, capitalism, dilemma of benevolence and justice, institutional crowding, sort-termism and depletion, AI and robots.

PFDN: Pyramid Feature Decoupling Network for Single Image Deraining.

Restoring images degraded by rain has attracted more academic attention since rain streaks could reduce the visibility of outdoor scenes. However, most existing deraining methods attempt to remove rain while recovering details in a unified framework, which is an ideal and contradictory target in the image deraining task. Moreover, the relative independence of rain streak features and background features is usually ignored in the feature domain. To tackle these challenges above, we propose an effective Pyramid Feature Decoupling Network (i.e., PFDN) for single image deraining, which could accomplish image deraining and details recovery with the corresponding features. Specifically, the input rainy image features are extracted via a recurrent pyramid module, where the features for the rainy image are divided into two parts, i.e., rain-relevant and rain-irrelevant features. Afterwards, we introduce a novel rain streak removal network for rain-relevant features and remove the rain streak from the rainy image by estimating the rain streak information. Benefiting from lateral outputs, we propose an attention module to enhance the rain-irrelevant features, which could generate spatially accurate and contextually reliable details for image recovery. For better disentanglement, we also enforce multiple causality losses at the pyramid features to encourage the decoupling of rain-relevant and rain-irrelevant features from the high to shallow layers. Extensive experiments demonstrate that our module can well model the rain-relevant information over the domain of the feature. Our framework empowered by PFDN modules significantly outperforms the state-of-the-art methods on single image deraining with multiple widely-used benchmarks, and also shows superiority in the fully-supervised domain.

State or Civil Society – What Matters in Fighting COVID-19? A Comparative Analysis of Hong Kong and Singapore

This article investigates the nuanced and disaggregated role of state and civil society in the fight against COVID-19 in Hong Kong and Singapore through a comparative policy study. Hong Kong and Singapore provide two contrasting cases of state-society interaction under the framework of Political Nexus Triads (PNT). Hong Kong combats COVID-19 with greater dependence on its civil society and bureaucrats, while Singapore relies more on a state-centred approach. They represent the diversity of state-society relations and multiple configurational causality in the COVID-19 responses and question the efficacy of any single and contextless model.

A Decade Long Slowdown in Road Crashes and Inherent Consequences Predicted for South Africa

Globally, there are 1.35 million road fatalities every year, which are estimated to cost governments approximately US$ 518 billion, making road fatalities the eighth leading cause of death across all age groups and the leading cause of death of children and young adults. In South Africa, despite tremendous governmental efforts to curb the soaring trajectory of road crashes, the annual number of road fatalities has increased by 26% in recent years. By fitting a structural equation model (SEM) and a GARCH Model (Generalized Auto-Regressive Conditional Heteroskedasticity) to analyze and predict future trend of road crashes (number of road crashes, number of casualties, number of fatal crashes and number of persons killed) in South Africa, we propose and test a complex metamodel that integrates multiple causality relationships. We show an increasing trend of road crashes over time, a trend that is predictable by number of vehicles in the country, the population of the country and the total distance travelled by vehicles. We further show that death rate linked to road crashes is on average 23.14 deaths per 100,000 persons. Finally, in the next decade, the number of road crashes is predicted to be roughly constant at 617,253 crashes but can reach 1,896,667 crashes in the worst-case scenario. The number of casualties was also predicted to be roughly constant at 93,531 over time, although this number may reach 661,531 in the worst-case scenario. However, although the number of fatal crashes may decrease in the next decade, it is forecasted to reach 11,241 within the next 10 years with the worse scenario estimated at 19,034 within the same period. At the same time, the number of persons killed in fatal crashes is also predicted to be roughly constant at 14,739 but may also reach 172,784 in the worse scenario. Overall, the present study reveals perhaps the positive effects of government initiatives to curb road crashes and their consequences; we call for more stronger actions for a drastic reduction in road accident events in South Africa.

A fuzzy-set qualitative comparative analysis of corruption and homicide in Organisation for Economic Co-operation and Development countries through the lens of the institutional anomie theory

Institutional Anomie Theory has been widely used in the study of criminal phenomena. Institutional Anomie Theory offers a macro explanation of crime because it locates the cause of crime in the anomie created by the combination of a cultural overemphasis on monetary success and restricted economic opportunity. In such a context, the economy dominates the social macrostructure and non-economic social institutions (family, education, polity) may counterbalance (Merton's approach) or reinforce (Messner and Rosenfeld's approach) economic pressures. Institutional Anomie Theory has been tested with multivariate regression and with multilevel modelling. Neither of these statistical approaches addresses the question of which combinations of institutions lead to criminal behaviour. This study attempts to fill this gap by using the fuzzy-set qualitative comparative analysis which allows multiple causality and asymmetric analysis of high and low crime rates. Based on the Institutional Anomie Theory theoretical model, this study demonstrates the existence of conditions for corruption and homicide in Organisation for Economic Co-operation and Development countries. The results are generally consistent with Merton's approach. It is shown that economic pressures combined with weak social institutions condition the extent of corruption and homicide in Organisation for Economic Co-operation and Development countries. However, there are differences between the two types of crime. The results also suggest that there is no symmetry in the causal combinations between high and low crime rates. The implications of these findings are discussed.

Landscape configuration mediates hydrology and nonpoint source pollution under climate change and agricultural expansion

Climate variability and landscape modifications directly influence watershed hydrology and processes of nonpoint source pollution, while remedial action requires distinguishing their effects. However, nonlinearity and multiple causality limit our ability to diagnose causes. Therefore, this study developed an approach that integrates hydrological modeling, random forests, regression trees, and variation partitioning analysis, to identify the effects of climate and landscape pattern changes upon runoff and nitrate loading in two typical watersheds in the Three Gorges Reservoir area of China. The Soil and Water Assessment Tool (SWAT) was used to track the spatiotemporal dynamics of runoff and nitrate loading (2000–2015). The findings showed that drylands and orchards were the dominant sources of nitrate and baseflow was the key mode of nitrate transport. Water yield and baseflow were mainly influenced by precipitation change, while the surface runoff and nitrate load were affected primarily by landscape pattern changes, especially in the wet season. Although ecological restoration programs have improved forest cover and forest fragmentation, the effects of forest restoration on the reduction of surface runoff and nitrate at the watershed scale have been offset by increased precipitation and agricultural expansion. Nevertheless, the role of landscape configuration is so dramatic that it can override variation in nitrate losses driven by changes in land cover and precipitation. Effective control of nitrate loss under intensive ecological restoration can be achieved by using a mosaic of “sink” patches to divide larger areas of cropland into smaller patches, maintaining cropland fragmentation, and limiting the increase in edge density of cropland. This paper’s proposed and implemented approach provides a new understanding of the interactions and nonlinear relationship between hydrological processes and environmental change, providing explicit ideas and useful insights for landscape planners and managers for improving eco-hydrological functions of watershed at the practical level. We emphasize that the impact of land use change cannot be assumed to be linear in restoration strategies, instead nonlinear impacts, clear details of landscape configuration, and seasonal climatic characteristics should be explicitly considered.

State or Civil Society – What Matters in Fighting COVID-19? A Comparative Analysis of Hong Kong and Singapore

This article investigates the nuanced and disaggregated role of state and civil society in the fight against COVID-19 in Hong Kong and Singapore through a comparative policy study . Hong Kong and Singapore provide two contrasting cases of state-society interaction under the framework of Political Nexus Triads (PNT). Hong Kong is combating COVID-19 with more dependence on its civil society and bureaucrats while Singapore relies more on a politician-led state approach. They represent the diversity of state-society relations and multiple configurational causality in COVID-19 responses and question the efficacy of any single and contextless model.

Diversas causas, similares resultados: reevaluando los medios y fines de la política de desarrollo empleando causalidad múltiple y capacidades

La política de desarrollo, como toda política pública, está basada en una fuerte noción de causalidad. Las intervenciones son implementadas con la expectativa de que producirán ‘desarrollo’. Dos elementos resultan relevantes. En primer lugar, dada la variedad de contextos y personas involucrados en estas intervenciones, es importante estudiar los supuestos asociados a los mecanismos causales que llevan a ciertos resultados, ya que, precisamente estos resultados dependen de los supuestos. En segundo lugar, el concepto de desarrollo que influye en la política pública debe ser discutido, pues no es solo una noción descriptiva sino también normativa. Por lo tanto, ambos elementos son analizados en este artículo, con el fin de contribuir a la formulación y análisis de la política pública. Con respecto a la causalidad, se argumenta a favor de la causalidad múltiple y se propone estudiarla a partir del uso del análisis cualitativo comparado con conjuntos difusos. Respecto al concepto de desarrollo, se argumenta a favor de un acercamiento enfocado en la gente. Para ello, se propone el enfoque de desarrollo humano y de las capacidades.