Abstract Rising sea levels pose a major threat to West Africa's densely populated and economically important coastal regions, which extend from Mauritania to Cameroon. Here, we explore the dynamics of Extreme Coastal Water Levels (ECWLs) from 1994 to 2015, with the aim of enhancing disaster management and prediction strategies. We found that regional differences in ECWL are primarily driven by tidal forces and wave runup, which have a direct impact on coastal erosion and floods, particularly in areas like Guinea-Bissau. This area is highly susceptible due to its wide low-lying coastal plains, which exacerbate the effects. Sea Level Anomalies (SLA) also play a critical role, as they reflect the cumulative effect of oceanographic and climatic conditions, exacerbating the impacts of tidal and wave dynamics. Although less significant, atmospheric contributions influence ECWL through storm surge and wind pattern variations. Regional climatic phenomena, particularly the Atlantic Niño, significantly influence the West African Monsoon, altering rainfall patterns and ECWL. In contrast, global climatic drivers such as the El Niño Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO) have a more subdued influence due to their less direct impact on local atmospheric conditions. Using a strategic cluster study based on annual tide and wave data, we categorise West African countries into distinct groups, enabling tailored and effective flood mitigation strategies that are aligned with their specific hydrodynamic and climatic characteristics. The study highlights the importance of tailored climate models and monitoring systems that focus on regional climate indicators such as the Atlantic Niño, which are essential for accurately predicting and managing the effects of climate changes on coastal areas in less developed countries.

This article uses comparative research on the tenant and trade union movements in Germany to discuss how these organizations foster solidarity. We explore the challenges and opportunities these movements face in fostering cooperation across diverse communities and workforces, as well as how they deal with everyday discrimination or authoritarian ideologies. Despite the fact that organizing fosters self-empowerment and improves material conditions, organizers grapple with societal divisions, prominently marked by racism. We present findings from our qualitative, empirical research on six different organizing projects. By identifying two strategic clusters, “All or nothing” and “The road is the reward,” derived from our empirical material, we illustrate the different strategies and their consequences for the organizations. In doing so, we offer a framework that can inform future organizing efforts seeking to strengthen relationships and address racism beyond formal political education.

ABSTRACT This paper addresses a very significant gap in maritime business literature by providing the first empirical study on the relationship between ESG performance and financial strategy. The previous literature acknowledges the importance of ESG but has mainly discussed how firms with different profiles of ESG behave financially, or their financial performances, in the maritime sector. A panel sample dataset comprising 94 publicly listed maritime companies over 2013–2024 is employed in this study to perform an integrated analysis at three levels (K-means typological clustering) based on both financial and ESG metrics/indicators. The analysis reveals three strategic clusters: (1) ‘Growth Champions,’ high performers on both ESG and profitability metrics; (2) ‘Balanced Operators,’ moderate levels of ESG with break-even financial performance; and (3) ‘Distressed Turnarounds,’ high disclosers on the ‘E’ pillar but poor financial results. One key finding is the clear shift to socially responsible strategies after 2020, indicating that the social aspect of ESG has transformed into a strategic tool aimed at enhancing long-term competitiveness and resilience. These results add subtle distinctions to the understanding of the role of ESG in financial strategy within the maritime sector. They also offer practical insight both for managers as well as policymakers.

Sustainable urban water management extends beyond technical infrastructure, relying on organizational capacity, effective governance and adaptive strategies that foster resilience and innovation. In many developing contexts, public water utilities face institutional and operational constraints that limit sustainable performance. This study examines organizational and governance determinants of water system effectiveness in Lagos, Nigeria, developing an empirical SEM-based framework to explain their interactions. Using a systematic review, expert interviews and a practitioner survey analyzed via Exploratory Factor Analysis and Partial Least Squares Structural Equation Modeling, the study identifies two core organizational dimensions—Operational Capability in Water Systems (OCWS) and Sustainability Governance and Innovation (SGI)—and three strategic clusters that enhance performance. Findings highlight the role of collaborative capacity, governance innovation, and cross-institutional coordination, aligning with sustainable infrastructure and organizational symbiosis principles. The framework advances existing sustainability models by integrating organizational capability and governance innovation into water utility performance assessment. Practical implications include strengthening institutional capacity, embedding innovation-focused governance mechanisms, and promoting inter-agency collaboration. Future research could apply this framework in other contexts or assess policy reforms that support resilient, sustainable urban water management.

Purpose This research study aims to develop a robust and ranking-based empirical framework for assessing supply chain resilience (SC-RS) through the identification, classification and validation of key driving factors. The study addresses critical gaps in existing SC-RS literature through the integration of multiple analytical techniques to evaluate the hierarchical relationships among resilience enablers. Design/methodology/approach Twelve critical drivers of SC-RS were identified through a systematic literature review (SLR) supported by theoretical synthesis and a structured survey of 283 respondents from industry and academia. The identified drivers are analyzed using interpretive structural modelling (ISM) to examine their associations and classified into four strategic clusters using MICMAC (Matrix of Cross Impact Multiplications Applied to Classification) technique relied in their driving and dependence power. The proposed conceptual model is subsequently validated by partial least squares structural equations modelling (PLS-SEM), which accesses the model’ reliability, convergent and divergent validity, and overall goodness-of-fits. Findings The findings of the study reveal that, with the use of a validated model, the firms can enhance their resilience by redesigning and optimizing their critical resources. The validated framework also provides firms with a data-driven basis for prioritization of resource allocation, optimize operational strategies and enhancing adaptive capabilities. Further, an integration of total quality management (TQM) principles into the resilience framework underscores the importance of process orientation and continuous improvement in achieving SC-RS. Research limitations/implications While this research work offers a theoretically sound and empirically tested framework, its generalizability is limited to the Indian Industrial setup. The future scholars could adopt a longitudinal or cross-national perspective, and can incorporate variables such as organization’ culture, digital maturity and agile partnership networking for more comprehensive understanding of SC-RS dynamics. Originality/value This research work contributes a novel and integrative methodological approach that connects the conceptual model and empirical validation of SC-RS. Further, by synthesizing ISM, MICMAC and PLS-SEM within a unified framework, the research provides unique strategic insights and operational tools for firms seeking to strengthen resilience across their supply chains (SCs). The framework’ relevance is further enhanced by the inclusion of TQM perspective, which encourages a balanced emphasis on process quality, resilience, and responsiveness in dynamic and changing business settings.

The rapid advancement of virtual reality (VR), augmented reality (AR), mixed reality (MR), and related technologies has catalysed the emergence of the metaverse as a promising environment for transforming teaching and learning. Technical and Vocational Education and Training (TVET), with its strong emphasis on hands-on and practice-oriented learning, is particularly well-positioned to benefit from immersive, interactive technologies. However, in Malaysia, little is known about how ready TVET educators are to adopt metaverse-related applications in their teaching, and what conditions would support or hinder such adoption. This study explores the readiness of metaverse-related applications for teaching and learning in Malaysian higher TVET education from the perspective of educators. A qualitative research design grounded in an interpretivist paradigm was employed. Semi-structured online interviews were conducted with five TVET educators from higher TVET institutions in Central Peninsular Malaysia. The interview protocol was adapted from prior work and conceptually structured using the Lokman Emotion and Importance Quadrant (LEIQ™) and the Technology Adoption Life Cycle (TALC) theories. Thematic analysis was used to analyse the data, leading to nine key themes grouped into four strategic clusters: assessing readiness for adoption, addressing challenges, leveraging enablers, and articulating a vision for future integration. The findings indicate that educators exhibit positive attitudes towards technology, perceive strong institutional support, and have access to basic technical infrastructure, suggesting conceptual readiness to adopt metaverse applications. Nevertheless, significant cost barriers and technical issues—such as hardware availability, scalability, maintenance, and connectivity—remain critical constraints. Training opportunities, institutional initiatives, and collaboration with industry emerged as powerful enablers. The analysis further suggests that metaverse adoption in Malaysian TVET currently lies in the “chasm” between early adopters and the early majority. The study concludes that strategic planning, sustained investment, and systematic capacity-building are essential to move metaverse applications from promising pilots to mainstream practice in TVET education.

Liquid additives represent a pivotal strategy for augmenting tribological performance, yet conventional research paradigms predominantly focus on adsorption and film-forming mechanisms while overlooking their influence on base lubricant properties. Herein, we demonstrate a sustainable liquid superlubricity system based on competitive hydrogen bonding, wherein poly(phosphoric acid) (PPA) serves as a ligand-competitive manipulator for choline chloride-based ionic liquid analogues (ILAs). Choline-based ILAs are inherently sustainable base lubricants because they are biodegradable, nontoxic, and derived from renewable sources. The intricate hydrogen bonding interactions and cluster evolution within PPA/ILAs systems were comprehensively elucidated through Raman spectra, 1H NMR, FTIR, and laser particle size analysis. Remarkably, PPA orchestrates dramatic enhancement in cluster particle size and distribution within the ILA matrix, amplifying asymmetric contact configurations while diminishing shear resistance during tribological processes. This synergistic effect enables spontaneous establishment of robust macroscopic superlubricity, manifesting an exceptionally low coefficient of friction (COF < 0.0032) that significantly reduces energy consumption and carbon emissions in mechanical systems. Furthermore, load-carrying capacity exhibits remarkable enhancement from 294 to 541 MPa, representing an 84% increase while extending equipment lifespan. This investigation unveils a transformative perspective on sustainable lubrication through green ILA systems and cluster particle size distribution dynamics, establishing innovative design paradigms for environmentally friendly next-generation liquid lubricant additives that promote sustainable industrial development.

BackgroundVerbal fluency tasks reveal consistent impairments among individuals with schizophrenia (SSD) and shed valuable insight on semantic and cognitive processing. However, comparisons with other psychiatric groups remain limited. Doing so may help clarify whether characteristics are unique to SSD versus shared across diagnoses. This study compared verbal fluency responses among participants with SSD, unipolar depression, and healthy volunteers (HV).MethodsParticipants with SSD (n = 64), unipolar depression (n = 70), and HVs (n = 37) completed letter- and category-guided verbal fluency tasks. Using automated pipelines, we extracted total correct responses, pause durations, first response latency, semantic and phonemic distances, and the number and size of semantic/phonemic clusters. Associations between fluency metrics and clinical ratings of speech disturbances (e.g., incoherence, inefficiency) were examined within patient groups.ResultsGroups differed significantly in total fluency scores, particularly on the category fluency task, with the greatest impairment in SSD and intermediate effects in depression. Significant pairwise group differences emerged in the number of semantic and phonemic clusters in the category task, while cluster size showed fewer differences. In HVs, both semantic and phonemic distances increased with longer pauses, suggesting strategic cluster switching. This pattern was absent in SSD and depression groups. SSD exhibited longer first latency and pauses relative to HVs; participants with depression showed no change in latency, but similarly prolonged pauses.ConclusionIndividuals with SSD and depression exhibit distinct patterns in verbal fluency, with category tasks revealing more robust group differences. Automated fluency analysis offers a scalable approach for differentially detecting cognitive-linguistic impairments across psychiatric populations.

This study aimed to address a critical gap by developing a strategic academic management strategy to systematically enhance digital literacy within public universities. Employing a sequential mixed-methods design, the research utilized a systematic SWOT analysis, collecting survey data from 190 academic leaders, to map internal capabilities against external influences. The analysis, detailed in the findings, identified Learning Media and Resources (PNImodified: 0.775) as the most significant overall internal weakness, particularly in digital awareness, while Measurement and Evaluation (PNImodified: 0.515) was the greatest strength. Externally, political factors (PNImodified: 0.541) emerged as the leading overall threat, contrasted by technological factors (PNImodified: 0.456) as the primary overall opportunity. These quantitative findings were systematically synthesized into a robust strategic quadrant matrix, which generated four essential strategic clusters SO, WO, ST, and WT to guide institutional action. The subsequent discussion elaborates on how this matrix facilitates the formulation of aggressive, turnaround, defensive, and cautious strategies, providing a contextually grounded and operationally actionable roadmap for academic leadership to proactively cultivate digitally literate graduates equipped for the modern workforce. Ultimately, the findings underscore the potential of academic management innovation to cultivate digitally competent graduates and strengthen institutional competitiveness in the era of rapid technological advancement.

Type of the article: Research Article AbstractMandatory reporting regulations challenge management adaptation. Organizational response patterns during regulatory transitions in emerging markets require further investigation. The study examines managerial responses of Thai-listed companies to the mandatory One Report regulation in 2021 and classifies firms into strategic clusters based on adaptation patterns to International Integrated Reporting Framework components. The paper used a comprehensive Integrated Reporting Quality Index and two-step cluster analysis on 232 annual reports from 58 largest companies in Thailand’s SET50 index (2019–2022) to move beyond simple compliance measurement and identify distinct managerial strategies and their organizational implications. Results demonstrate significant improvement in the quality of managerial responses to the regulation, representing a 36.4% increase, from moderate levels (X̄ = 1.21, SD = 0.24) before implementation to high levels (X̄ = 1.65, SD = 0.18) afterward. Wilcoxon signed-rank tests confirmed statistical significance (Z values between –3.205 and –5.526, p &amp;amp;lt; 0.001). Notably, cluster analysis identifies two distinct strategic approaches: Strategic adopters (Cluster 1), who demonstrate comprehensive integrated thinking, and compliance-oriented responders (Cluster 2), who adopt minimalist approaches. The study reveals significant organizational learning over the study period, with strategic adopters growing from 27 to 44 companies (46.6% to 75.9%) while compliance-oriented responders declined from 31 to 14 companies (53.4% to 24.1%). Mandatory implementation successfully catalyzed strategic differentiation, though challenges in disclosing non-financial capital persist. These findings provide crucial insights for managers seeking competitive advantage during regulatory transitions and for policymakers designing effective governance frameworks.

Purpose Flooding poses a critical threat to buildings and infrastructure in Nigeria, exacerbated by rapid urbanization, inadequate drainage systems and climate change. Despite the severity of this issue, existing flood prevention measures remain fragmented and ineffective. This study aims to explore innovative strategies to enhance flood resilience in buildings and infrastructure, offering sustainable, cost-effective and scalable solutions tailored to Nigeria’s built environment. Design/methodology/approach A mixed-methods approach was adopted, integrating qualitative and quantitative analyses. Subject matter experts and flood-affected residents in Lagos and Anambra were interviewed using a semi-structured approach, while construction professionals and residents were administered structured questionnaires. Statistical techniques, including the Kruskal–Wallis H-test and exploratory factor analysis, were used to identify and validate key strategies. Findings Four strategic clusters emerged: structural adaptations; natural and green infrastructure; water management and mitigation; and planning and community strategies. These clusters provide a holistic framework for flood prevention, incorporating sustainable design, advanced construction techniques and community-driven initiatives. Practical implications This study advocates for integrating flood-resistant materials, green infrastructure and participatory flood management into existing governance frameworks. Addressing institutional and financial constraints is crucial to scaling these interventions across Nigeria. Originality/value This study offers actionable insights for policymakers, urban planners and construction stakeholders. It presents a localized yet adaptable approach to flood prevention, serving as a model for other developing nations facing similar challenges.

The article examines theoretical approaches to managing agrarian clusters, a pressing task for Ukraine in the context of global competition and the need for innovative development of the agricultural sector. Agrarian clusters are identified as one of the most promising organizational and economic forms, contributing to the strengthening of cooperation, technology transfer, and increased competitiveness. The work aims to generalize and systematize existing theoretical concepts of cluster management and substantiate their practical application in Ukrainian realities. The paper analyzes key approaches to managing cluster formations, specifically systemic, institutional, innovation-network, project-oriented, and agro-ecological approaches. Their comparative characteristics are examined, and the advantages and limitations of each of them are highlighted. Michael Porter's classical cluster theory is studied, noting its fundamental contribution, while also highlighting the need for more attention to agricultural specifics. The primary outcome of the study is the development of an integrative model for agrarian cluster management, tailored to modern Ukrainian conditions. This model combines economic integration, institutional support, information and innovation exchange, and state regulation. It takes into account such challenges as uneven regional development, a lack of special cluster legislation, a low level of trust between agrarians, and the consequences of martial law, particularly the disruption of logistics. The model involves the creation of a strategic cluster center, the involvement of key stakeholders (producers, processors, scientific institutions, and financial institutions), and the establishment of a favorable institutional environment. It is emphasized that for Ukraine, the most appropriate approach is a comprehensive, hybrid one that combines elements of systemic, institutional, network, and project concepts. Effective management of agrarian clusters based on the proposed model can become a key factor in increasing the competitiveness of not only individual enterprises but also entire regions, contributing to the sustainable development of rural areas.

Introduction: Despite growing interest in halal research, there is a lack of complete understanding regarding the strategic contribution of the halal value chain to business performance and operations. Issues such as fragmented regulations and limited standardization beyond the food sector exacerbate this. This study aims to systematically analyze the evolution of halal value chain topics within academic discourse, identifying trends, evaluating the impact of research, recognizing key contributors, and suggesting directions for future research. Methods: This study adopts a bibliometric analysis methodology. The study analyzed 233 Scopus and 116 Web of Science-indexed research publications. The export data is then processed and analyzed using R-studio software to determine the bibliometric map of the halal value chain. Results: The findings demonstrate a significant increase in halal value chain research since 2011, with a primary concentration in Southeast Asia and a focus on micro, small, and medium-sized enterprises (MSMEs) and the halal food industry. Researchers have identified the gaps in non-food halal sectors, including cosmetics, pharmaceuticals, finance, and tourism. The analysis also highlights three strategic clusters—governance and certification, technological and operational integration, and market-oriented strategies—each contributing to economic, operational, and ethical outcomes. Conclusion and Suggestion: This study reveals that adopting a value chain perspective in halal supply chain management necessitates a comprehensive and integrated strategy. Future research should focus on empirical studies, sectoral diversification, and innovation in digital halal assurance to enhance the sustainability of the global halal ecosystem.

PurposeThere is seemingly lack of understanding of strategic attributes of architectural services firms and their performance dimensions in the wake of continuous poor service delivery in public procurement in Ghana. The study explores possible strategic groupings of Architectural service firms and their performance in public procurement in Ghana.Design/methodology/approachThe study adopted a deductive questionnaire survey and the questionnaire was developed using Porter’s (1980) generic strategies and Prakash and Phadtare (2018) validated service quality scale for architects. The data was subsequently analysed using the k-means cluster analysis technique as it is suitable for identifying groupings that exhibit and share similar characteristics.FindingsThe results revealed four strategic cluster in architectural services. It further revealed that, there is significant differences among the firms across the differentiation, cost leadership and focus strategic attributes and this also influenced their service quality performance on the six performance attributes. The attributes were quality of design, quality of project administration, quality of communication, quality of relationship, dependability quality and delivery quality performances.Originality/valueThe understanding provided by the study can help architectural firms to pursue and legitimise strategic orientations that can optimise their performance of service quality in public procurement in Ghana. This can be aided by continuous analysis of their operating environment and make strategic decisions for their growth in public procurement markets in Ghana.

Identifying the scriptwriter in historical manuscripts is crucial for historians, providing valuable insights into historical contexts and aiding in solving historical mysteries. This research presents a robust deep learning system designed for classifying historical manuscripts by writer, employing intelligent feature selection and vision transformers. Our methodology meticulously investigates the efficacy of both handcrafted techniques for feature identification and deep learning architectures for classification tasks in writer identification. The initial preprocessing phase involves thorough document refinement using bilateral filtering for denoising and Otsu thresholding for binarization, ensuring document clarity and consistency for subsequent feature detection. We utilize the FAST detector for feature detection, extracting keypoints representing handwriting styles, followed by clustering with the k-means algorithm to obtain meaningful patches of uniform size. This strategic clustering minimizes redundancy and creates a comprehensive dataset ideal for deep learning classification tasks. Leveraging vision transformer models, our methodology effectively learns complex patterns and features from extracted patches, enabling precise identification of writers across historical manuscripts. This study pioneers the application of vision transformers in historical document analysis, showcasing superior performance on the “ICDAR 2017” dataset compared to state-of-the-art methods and affirming our approach as a robust tool for historical manuscript analysis.

Despite their constrained discursive space, defendants in Chinese criminal trials often resist interrogators’ domination in pursuit of favorable judgments. This article delves into defendants’ deployment of discursive resistance strategies and strategic clusters in courtroom interaction and examines the impact of gender, education, and penalty on strategic choices. A corpus of Chinese criminal trial discourse, totaling 15,388 minutes of recordings and 3.3 million transcribed Chinese characters, was constructed for analysis. Quantitative and qualitative analysis demonstrate that defendants’ discursive practice are predominantly characterized by covert resistance strategies, supplemented by overt resistance strategies, and their strategic clusters demonstrate marked preferential patterns, generating synergistic resistance effects that optimize defensive efficacy. Additionally, gender, education and penalty significantly shape strategic choices, with the impact of penalty particularly pronounced. This study elucidates the bidirectional operation of power between dominant and subordinate parties in courtrooms, providing valuable insights particularly for research on conflict-laden institutional interactions.

This study presents a comprehensive bibliometric analysis of railway safety research from 2019 to 2024, offering critical insights into the thematic evolution, intellectual structure, and future pathways in this vital domain. By analyzing 445 peer-reviewed articles retrieved from leading academic databases, the study identifies major research clusters centered around risk assessment, human factors, and AI-enabled infrastructure monitoring. The findings reveal a significant shift toward intelligent safety systems, with deep learning, predictive maintenance, and human reliability modeling emerging as dominant themes. China, the United Kingdom, and India are identified as leading contributors, with strong international collaboration driving innovation in the field. Despite notable progress, the analysis uncovers persistent gaps—particularly in cybersecurity resilience, cognitive integration in risk assessment, infrastructure adaptation to climate risks, and localization technologies for autonomous train systems. Future research directions are proposed to address these gaps, including multi-sensor fusion for train positioning, AI-based decision-making frameworks for autonomous operations, and integration of human factors into machine learning-based safety evaluations.

Corporate Social Responsibility (CSR) and its sustainability-focused communications are now recognized as essential corporate activities. As society increasingly holds firms accountable for their social, environmental, and sustainability impacts, academic interest in CSR communications has similarly grown, with scholars exploring how CSR communication influences stakeholder engagement and corporate strategies. In response to this growing interest, we conducted a systematic literature review utilizing bibliometric analysis to identify and examine publication trends and patterns in CSR and CSR-associated communications, drawing from a robust dataset of 3513 documents extracted from Scopus and Web of Science. The analysis was conducted using the Biblioshiny R package and Excel to ensure methodological precision and analytical depth. We explored the characteristics of publications related to topics such as business, authorship, and journals over a four-decade period spanning from 1984 to 2024. Our results reveal four strategic clusters of CSR disclosure, reflecting a shift from symbolic to strategic and stakeholder-focused communication. Thematic evolution highlights the growing integration of ESG frameworks and digital reporting practices. This study is significant not only in its methodological rigor but also in its timely contribution to the intersection of CSR, sustainability, and strategic communication. Also, this study introduces a new theoretical framework through the CSR strategic disclosure indicator metric, which connects the level of disclosure maturity with the focus on different stakeholder groups. We discuss the implications of our findings not only for future scholarly research in CSR but also for corporate sustainability practitioners who look to academia for insights on emerging trends in CSR and CSR reporting.

The construction industry is globally recognized as one of the fastest-growing sector contributing directly and indirectly to the development of several other sectors of the economy. Despite its significance importance, and based on persistently reasons, the industry has often overwhelmingly with various challenges including inability to finish the road construction projects within a given schedule. That is road construction delays. This study aimed to examine the stakeholder’s perception on prevailing best practice measures to reduce construction projects delay in Tanzania. The study adopted the questionnaire tool and the survey interview to collect the respondent’s opinion from 208 respondents having experience of more than five years obtained through purposive sampling. The mean scores and the relative importance index (RII) of the data were computed using SPSS 24 tool to obtain the descriptive information and inferential statistics. The findings have revealed ten potential factors for construction project delays and thirteen best practices that whenever implemented can assists to minimize delays. The identified best practice measures were categorized in clusters to indicate the project participants who plays the significant role in minimizing the delays. The current study proposes the future research to focus on identifying the relationship between the strategic cluster categories in identifying which cluster category correlate highly towards minimizing the construction project delays.

How do workers conceptualize a platform’s algorithm and adjust their practices to its logic? To pursue this question, we draw on an ethnography of Grab, the leading rideshare platform in Southeast Asia, composed of 60+ trips talking to drivers on the back of bikes in Hanoi, and in-depth interviews with 10 drivers. From this rich material, we identify a strategic cluster of practices that we term “taming the algorithm.” Taming requires three key moves: iteratively adapting behaviors to algorithmic pressures (improvisation), juggling competing demands to deliver a productive performance at bodily limits (scrambling), and repeating these activities over time until they become a baseline in the system (enduring). If done successfully, these moves establish routinized productivity, a pattern of algorithmically ideal labor that means the platform will consistently delegate tasks to the worker. Taming is inherently double-edged, an exhausting form of self-exploitation that nevertheless provides some predictability and agency to workers. Taming the algorithm offers a contribution on two fronts. First, it allows us to prise the ontological and the technical aspects of platform labor apart: these moves are risky, brutal, and chaotic for workers but are smoothed into desirable integers and patterns by the algorithm. Secondly, it articulates a minor freedom between the twin poles of Freedom and Unfreedom as conventionally understood, showing how workers achieve some agency and some perception of power without fundamentally disrupting the systemic inequalities maintained by platform logics.