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This article problematizes the concept of freedom rooted in liberalism, examining the detention of historian Ilan Pappe by the Federal Bureau of Investigation (FBI) at Detroit Airport in the United States as an emblematic case study.

The research adopts a methodological triangulation approach, based on an analysis that combines data about the event and theories about the concept of freedom, problematizing authors who focused on the relationship between the individual and society in a liberal context, where individualism serves as the basis for specific conceptions of social relations.

Through the use of authors such as John Stuart Mill and John Locke, as well as the contributions of authors like Norbert Elias, it is argued that true freedom is relational, rooted in social interdependencies and the social construction of an individuality that is not individualistic but intrinsically linked to collective aspects.

Pappe’s case illustrates the tensions between individual freedom and collective interests, highlighting the need to reassess freedom of expression in complex political and social contexts.

This article proposes a more inclusive and interconnected view of human freedom, where individual and collective interests are negotiated within a dynamic web of social relations.

The purpose of this study is to analyze the seasonal spatiotemporal climate variability in the Borena zone of Ethiopia and its effects on agriculture and livestock production. By examining these climate variables in relation to global sea surface temperatures (SST) and atmospheric pressure systems, the study seeks to understand the underlying mechanisms driving local climate variability. Furthermore, it assesses how these climate variations impact crop yields, particularly wheat and livestock production, providing valuable insights for developing effective adaptation strategies and policies to enhance food security and economic stability in the region.

The design and methodology of this study involve a multifaceted approach to analyzing seasonal spatiotemporal climate variability in the Borena zone of Ethiopia. The research uses advanced statistical techniques, including rotated empirical orthogonal function (EOF) and rotated principal component analysis (RPCA), to identify and quantify significant patterns in seasonal rainfall, temperature and drought indices over the period from 1981 to 2022. These methods are used to reveal the spatiotemporal variations and trends in climate variables. To understand the causal mechanisms behind these variations, the study correlates seasonal rainfall data with global SST and examines atmospheric pressure systems and wind vectors. In addition, the impact of climate variability on agricultural and livestock production is assessed by linking observed climate patterns with changes in crop yields, particularly wheat and livestock productivity. This comprehensive approach integrates statistical analysis with environmental and agricultural data to provide a detailed understanding of climate dynamics and their practical implications.

The findings of this study reveal significant seasonal spatiotemporal climate variability in the Borena zone of Ethiopia, characterized by notable patterns and trends in rainfall, temperature and drought indices from 1981 to 2022. The analysis identified that over 84% of the annual rainfall occurs during the March to May (MAM) and September to November (SON) seasons, with MAM contributing approximately 53% and SON over 31%, highlighting these as the primary rainfall periods. Significant spatiotemporal variations were observed, with northwestern (35.4%), southern (34.9%) and northeastern (19.3%) are dominant variability parts of the zone during MAM season, similarly southeastern (48.7%), and northcentral (37.8%) are dominant variability parts of the zone during SON season. Trends indicating that certain subregions experience more pronounced changes in climate variables in both seasons. Correlation with global SST and an examination of atmospheric pressure systems elucidated the mechanisms driving these variations, with significant correlation with the southern and central part of Indian Ocean. This study also found that fluctuations in climate variables significantly impact crop production, particularly wheat and livestock productivity in the region, underscoring the need for adaptive strategies to mitigate adverse effects on agriculture and food security.

The implications of this study highlight the need for robust adaptation strategies to mitigate the effects of climate variability. Detailed research on seasonal climate patterns and the specific behaviors of livestock and crops is essential. Gaining a thorough understanding of these dynamics is critical for developing resilient adaptation strategies tailored to the unique ecological and economic context of the Borana zone. Future research should focus on seasonal climate variations and their implications to guide sustainable development and livelihood adjustments in the region.

This study offers significant originality and value by providing a detailed analysis of seasonal spatiotemporal climate variability in the Borena zone of Ethiopia, using advanced statistical techniques such as rotated EOF and RPCA. By integrating these methods with global SST data and atmospheric pressure systems, the research delivers a nuanced understanding of how global climatic factors influence local weather patterns. The study’s novel approach not only identifies key trends and patterns in climate variables over an extensive historical period but also links these findings to practical outcomes in crop and livestock production. This connection is crucial for developing targeted adaptation strategies and policies, thereby offering actionable insights for enhancing agricultural practices and food security in the region. The originality of this work lies in its comprehensive analysis and practical relevance, making it a valuable contribution to both climate science and regional agricultural planning.

This paper aims to reconcile conflicting findings about the role of corporate social responsibility (CSR) in counteracting the negative impacts of brands’ ethical transgressions by testing the moderating role of self-brand connection (SBC).

Drawing on motivated reasoning theory, this paper posits that high- and low-SBC consumers’ information processing and moral judgment are driven by distinct goals: to reach desired versus accurate conclusions, respectively. Five experiments were conducted to test whether CSR efforts can mitigate the impact of blatant ethical transgressions.

CSR allows high-SBC consumers to evaluate brand transgressions more favorably, as CSR serves as counterfactual evidence that reinforces their beliefs in the brand’s morality. In contrast, low-SBC consumers view CSR as hypocritical, leading to more negative responses. Increased perceptions of brand morality (hypocrisy) mediate CSR’s buffering (backfiring) effects among high- (low-) SBC consumers.

This paper does not control for the effect of the time gap between CSR and ethical transgressions even if buffering effects of CSR could be faded out as memories recede.

Brand transgressions may be inevitable events, but firms or managers can alleviate the negative impact of transgressions by engaging in CSR activities. In doing so, they need to make clear to whom they will appeal using CSR information considering its backfiring effects among low-SBC consumers.

Few studies have examined when and how CSR attenuates or exacerbates the negativity of brand transgressions with a strong theoretical framework. This paper, grounded in motivated reasoning theory, explains how the same CSR initiative can yield opposing outcomes based on the consumer’s self-brand connection. Rather than solely exploring how strong consumer-brand relationships buffer brand transgressions, this research shows how high-SBC consumers biasedly seize CSR information to justify brand transgressions, even when they are blatant.