This revised edition makes Finnegan’s ground-breaking research available to the next generation of scholars. It includes a new introduction, additional images and an updated bibliography, as well as its original chapters on poetry, prose, "drum language” and drama, and an overview of the social, linguistic and historical background of oral literature in Africa. This volume is complemented by original recordings of stories and songs from the Limba country (Sierra Leone), collected by Finnegan during her fieldwork in the late 1960s,
This study examines the social representation of drug abuse in Brian Makara’s poem “Sethethefatsi.” The prevalence of drug abuse among South African township youth has increased dramatically. This has resulted in the development of diverse intervention techniques at multiple levels across the country. In response to the drug endemic, literary writers like Makara use their art to raise awareness of this pervasive issue. This study argues that poetry serves as a valuable medium for exploring social phenomena because literature often reflects societal experiences. This study is underpinned by the theory of the sociology of literature, which views poetry as a reflection of society, social commentary, and the expression of a collective’s consciousness. This research adopts a desktop qualitative research approach to analyse how drugs are represented in Makara’s poem. The findings reveal that Makara personifies drugs for two reasons: (a) to portray drugs as an “individual” with harmful intentions infiltrating society; and (b) to depict drugs as a product of those who undermine societal values, whose intention is to obstruct societal development and sustainability. The study demonstrates that literary texts are valuable sources that engage with societal issues. Furthermore, the study signals that the contemporary Sesotho literature critically examines societal challenges that warrant political and policy interventions.
In this article, I examine various dimensions of displacement resulting from the environmental crisis envisaged in the speculative debut novel of the South African author Alistair Mackay: It Doesn’t Have To Be This Way (2022). The theoretical framework is located in the area of posthumanist studies but also involves elements of trauma theory, as the issue of psychological displacement is viewed through E. Ann Kaplan’s concept of pre-trauma, a paralysing anxiety about the future disaster evoked by the scenarios of the near apocalypse. I also offer a brief review of the political and economic conditions of post-apartheid South Africa, discussing the country’s adoption of neoliberal tenets. Since Mackay’s novel represents climate change as the result of ecologically hazardous activities of multinational corporations which stem from their colonial/imperialist commodification of the natural environment, my analysis draws from ecocritical African studies and contemporary critiques of capitalism, thus situating the climatic catastrophe of the Anthropocene in the context of destructive practices of the neoliberalist economy. Furthermore, in this article, I employ the posthumanist perspective (Hayles; Braidotti) to discuss the issue of body augmentation, presenting the reservations of Mackay’s characters towards dehumanising effects of integrating our bodies with ultramodern technologies. Finally, a pro-active ecological endeavour of tree-planting is examined in the context of Donna Haraway’s notion of the Chthulucene as well as a long-standing African appreciation of the forest—as a biological asset, regulating climate and farming, and as a spiritual one, the abode of deities.
Lukman Jibril Aliyu, Umar Sani Muhammad, Bilqisu Ismail
et al.
Wildlife populations in Africa face severe threats, with vertebrate numbers declining by over 65% in the past five decades. In response, image classification using deep learning has emerged as a promising tool for biodiversity monitoring and conservation. This paper presents a comparative study of deep learning models for automatically classifying African wildlife images, focusing on transfer learning with frozen feature extractors. Using a public dataset of four species: buffalo, elephant, rhinoceros, and zebra; we evaluate the performance of DenseNet-201, ResNet-152, EfficientNet-B4, and Vision Transformer ViT-H/14. DenseNet-201 achieved the best performance among convolutional networks (67% accuracy), while ViT-H/14 achieved the highest overall accuracy (99%), but with significantly higher computational cost, raising deployment concerns. Our experiments highlight the trade-offs between accuracy, resource requirements, and deployability. The best-performing CNN (DenseNet-201) was integrated into a Hugging Face Gradio Space for real-time field use, demonstrating the feasibility of deploying lightweight models in conservation settings. This work contributes to African-grounded AI research by offering practical insights into model selection, dataset preparation, and responsible deployment of deep learning tools for wildlife conservation.
While a language assigns a value of either `yes' or `no' to each word, a lattice language assigns an element of a given lattice to each word. An advantage of lattice languages is that joins and meets of languages can be defined as generalizations of unions and intersections. This fact also allows for the definition of positive varieties -- classes closed under joins, meets, quotients, and inverse homomorphisms -- of lattice languages. In this paper, we extend Pin's positive variety theorem, proving a one-to-one correspondence between positive varieties of regular lattice languages and pseudo-varieties of finite ordered monoids. Additionally, we briefly explore algebraic approaches to finite-state Markov chains as an application of our framework.
There is a growing interest in developing strong biomedical vision-language models. A popular approach to achieve robust representations is to use web-scale scientific data. However, current biomedical vision-language pretraining typically compresses rich scientific figures and text into coarse figure-level pairs, discarding the fine-grained correspondences that clinicians actually rely on when zooming into local structures. To tackle this issue, we introduce Panel2Patch, a novel data pipeline that mines hierarchical structure from existing biomedical scientific literature, i.e., multi-panel, marker-heavy figures and their surrounding text, and converts them into multi-granular supervision. Given scientific figures and captions, Panel2Patch parses layouts, panels, and visual markers, then constructs hierarchical aligned vision-language pairs at the figure, panel, and patch levels, preserving local semantics instead of treating each figure as a single data sample. Built on this hierarchical corpus, we develop a granularity-aware pretraining strategy that unifies heterogeneous objectives from coarse didactic descriptions to fine region-focused phrases. By applying Panel2Patch to only a small set of the literature figures, we extract far more effective supervision than prior pipelines, enabling substantially better performance with less pretraining data.
Alioune Diallo, Aicha War, Moustapha Awwalou Diouf
et al.
The West African Economic and Monetary Union (WAEMU) states, characterized by widespread smartphone usage, have witnessed banks and financial institutions introducing mobile banking applications (MBAs). These apps empower users to perform transactions such as money transfers, bill payments, and account inquiries anytime, anywhere. However, this proliferation of MBAs also raises significant security concerns. Poorly implemented security measures during app development can expose users and financial institutions to substantial financial risks through increased vulnerability to cyberattacks. Our study evaluated fifty-nine WAEMU MBAs using static analysis techniques. These MBAs were collected from the 160 banks and financial institutions of the eight WAEMU countries listed on the Central Bank of West African States (BCEAO) website. We identified security-related code issues that could be exploited by malicious actors. We investigated the issues found in the older versions to track their evolution across updates. Additionally, we identified some banks from regions such as Europe, the United States, and other developing countries and analyzed their mobile apps for a security comparison with WAEMU MBAs. Key findings include: (1) WAEMU apps exhibit security issues introduced during development, posing significant risks of exploitation; (2) Despite frequent updates, underlying security issues often persist; (3) Compared to MBAs from developed and developing countries, WAEMU apps exhibit fewer critical security issues; and (4) Apps from banks that are branches of other non-WAEMU banks often inherit security concerns from their parent apps while also introducing additional issues unique to their context. Our research underscores the need for robust security practices in WAEMU MBAs development to enhance user safety and trust in financial services.
Background In nursing students, high stress levels can lead to burnout, anxiety, and depression. Our objective is to characterize the epidemiology of perceived stress, stressors, and coping strategies among nursing students in the Middle East and North Africa region. Methods We conducted an overview of systematic reviews. We systematically searched PubMed, Embase, PsycInfo, and grey literature sources between January 2008 and June 2020 with no language restrictions. We included any systematic review reporting measurable stress-related outcomes including stress prevalence, stressors, and stress coping strategies in nursing students residing in any of the 20 Middle East and North Africa countries. We also included additional primary studies identified through a hand search of the reference lists of relevant primary studies and systematic reviews. Results Seven systematic reviews and 42 primary studies with data from Bahrain, Egypt, Iraq, Jordan, Oman, Pakistan, Palestine, Saudi Arabia, and Sudan were identified. Most studies included nursing students undergoing clinical training. The prevalence range of low, moderate, and high perceived stress among nursing students was 0.8–65%, 5.9–84.5%, and 6.7–99.2%, respectively. Differences related to gender, training period, or the type of tool used to measure stress remain unclear given the wide variability in the reported prevalence measures across all stress levels. Common clinical training stressors were assignments, workload, and patient care. Academic training-related stressors included lack of break/leisure time, low grades, exams, and course load. Nursing students utilized problem focused (dealing with the problem), emotion focused (regulating the emotion), and dysfunctional (venting the emotions) stress coping mechanisms to alleviate their stress. Conclusions Available data does not allow the exploration of links between stress levels, stressors, and coping strategies. Limited country-specific prevalence data prevents comparability between countries. Reducing the number or intensity of stressors through curriculum revision and improving students’ coping response could contribute to the reduction of stress levels among students. Mentorship, counseling, and an environment conducive to clinical training are essential to minimize perceived stress, enhance learning, and productivity, and prevent burnout among nursing students.
Linlin Zhang, Derrick Ssewanyana, Marie-Claude Martin
et al.
Background: Over 250 million children in low- and middle-income countries are at risk of not achieving their fullest developmental potential due to co-occurring risks such as poor nutrition and inadequate learning opportunities. Early intervention programs integrating the aspects of nurturing care, that is, good health, adequate nutrition, safety and security, responsive caregiving, and learning opportunities, may ameliorate against the negative impact of these adverse conditions. Methods: This meta-analytic review updates the evidence base of parenting interventions comprising stimulation and responsive caregiving components on developmental outcomes for children under age 2 years in low- and middle-income countries. It also describes and assesses the moderation effects of population characteristics and implementation features on the intervention effectiveness. Studies were identified based on previous systematic reviews and an updated literature search in eight databases and the gray literature up to December 2020. A random-effect model was used to explore the pooled effect sizes accounted for by the intervention for developmental outcome of cognition, language, motor, and social-emotional capacities. Exploratory moderation analyses were also conducted. Results: Twenty-one randomized controlled trials representing over 10,400 children from 12 low- and middle-income countries and regions across three continents (Africa, Latin America, and Asia) were identified. The interventions showed overall small-to-moderate effects on children's cognitive development (ES = 0.44; 95% CI = [0.30, 0.57]); language development (ES = 0.33; 95% CI = [0.18, 0.49]); and motor skills (ES = 0.21; 95% CI = [0.10, 0.32]). The overall effect on social-emotional development was non-significant (ES = 0.17; 95% CI = [−0.01, 0.34]). Effect sizes (ES) varied significantly across the studies. Parenting programs that targeted vulnerable groups, including rural communities and caregivers with lower education levels, had more significant effects on children's development. Group sessions (vs. individual visits) and high program dose (≥12 sessions) were also associated with stronger effects on child development. Further research is needed to determine the effectiveness of the workforce and training on programmatic outcomes. Conclusion: The findings indicate that parenting interventions that encourage nurturing care are effective in improving the early development of children, especially among vulnerable populations. We discuss opportunities to strengthen the implementation of research-based parenting interventions in such contexts.
Gabriel Orlanski, Kefan Xiao, Xavier Garcia
et al.
Current benchmarks for evaluating neural code models focus on only a small subset of programming languages, excluding many popular languages such as Go or Rust. To ameliorate this issue, we present the BabelCode framework for execution-based evaluation of any benchmark in any language. BabelCode enables new investigations into the qualitative performance of models' memory, runtime, and individual test case results. Additionally, we present a new code translation dataset called Translating Python Programming Puzzles (TP3) from the Python Programming Puzzles (Schuster et al. 2021) benchmark that involves translating expert-level python functions to any language. With both BabelCode and the TP3 benchmark, we investigate if balancing the distributions of 14 languages in a training dataset improves a large language model's performance on low-resource languages. Training a model on a balanced corpus results in, on average, 12.34% higher $pass@k$ across all tasks and languages compared to the baseline. We find that this strategy achieves 66.48% better $pass@k$ on low-resource languages at the cost of only a 12.94% decrease to high-resource languages. In our three translation tasks, this strategy yields, on average, 30.77% better low-resource $pass@k$ while having 19.58% worse high-resource $pass@k$.
Background Learners living with hearing impairment are at a higher risk of visual impairment. Purpose To summarise relevant literature investigating the prevalence and causes of visual impairment amongst learners living with hearing impairment in sub-Saharan Africa. Methods A search of nine databases and the reference lists of retrieved studies were conducted using the standard methodology for scoping reviews as described in the PRISMA statement. The databases were MEDLINE, PubMed, EMBASE, the Cochrane Library, Global Health, OVID, Google Scholar, Web of Science, and Science Direct. A scoping review of articles published in the English language from 2000 to 2020 was conducted while considering the study design, sub-Saharan Africa, and school for the deaf. Descriptive statistics was used to analyse the data. Results The initial search retrieved eight studies, seven of which met the set inclusion criteria. All seven studies included employed a cross-sectional design. The prevalence of visual impairment ranged from 2.2–34.6% with the major cause being uncorrected refractive error (7.9–73.26%). The most common type of refractive error was myopia (42.2%) followed by hyperopia (28.6%) and astigmatism (28.6%). Conclusion This review has demonstrated that there is a paucity of high-quality and well-designed studies that have investigated the prevalence and causes of visual impairment amongst hearing-impaired children in sub-Saharan Africa suggesting the need for further research in this area.
Giovanni Sileno, Thomas van Binsbergen, Matteo Pascucci
et al.
Several solutions for specifying normative artefacts (norms, contracts, policies) in a computational processable way have been presented in the literature. Legal core ontologies have been proposed to systematize concepts and relationships relevant to normative reasoning. However, no solution amongst those has achieved general acceptance, and no common ground (representational, computational) has been identified enabling us to easily compare them. Yet, all these efforts share the same motivation of representing normative directives, therefore it is plausible that there may be a representational model encompassing all of them. This presentation will introduce DPCL, a domain-specific language (DSL) for specifying higher-level policies (including norms, contracts, etc.), centred on Hohfeld's framework of fundamental legal concepts. DPCL has to be seen primarily as a "template", i.e. as an informational model for architectural reference, rather than a fully-fledged formal language; it aims to make explicit the general requirements that should be expected in a language for norm specification. In this respect, it goes rather in the direction of legal core ontologies, but differently from those, our proposal aims to keep the character of a DSL, rather than a set of axioms in a logical framework: it is meant to be cross-compiled to underlying languages/tools adequate to the type of target application. We provide here an overview of some of the language features.
Language is the primary medium through which stereotypes are conveyed. Even when we avoid using derogatory language, there are many subtle ways in which stereotypes are created and reinforced, and they often go unnoticed. Linguistic bias, the systematic asymmetry in language patterns as a function of the social group of the persons described, may play a key role. We ground our study in the social psychology literature on linguistic biases, and consider two ways in which biases might manifest: through the use of more abstract versus concrete language, and subjective words. We analyze biographies of African American and Caucasian actors at the Internet Movie Database (IMDb), hypothesizing that language patterns vary as a function of race and gender. We find that both attributes are correlated to the use of abstract, subjective language. Theory predicts that we describe people and scenes that are expected, as well as positive aspects of our in-group members, with more abstract language. Indeed, white actors are described with more abstract, subjective language at IMDb, as compared to other social groups. Abstract language is powerful because it implies stability over time; studies have shown that people have better impressions of others described in abstract terms. Therefore, the widespread prevalence of linguistic biases in social media stands to reinforce social stereotypes. Further work should consider the technical and social characteristics of the collaborative writing process that lead to an increase or decrease in linguistic biases.
ABSTRACT South Africa remains beset by protest. Notwithstanding an impressive literature, quantifying protests remains problematic; most attempts extrapolate from samples or media-derived data sets. Applying machine learning to the world’s largest publicly available, single-country public-event database – the South African Police Service’s Incident Registration Information System – the article classifies 150,000 events into type and levels of ‘tumult’. The author provides the first holistic picture of all police-reported protest in South Africa over a given period (1997–2013), showing a count increase (partly confirming the ‘rebellion of the poor’ thesis), while more nuanced measures (i.e. protestors per capita) demonstrate a less urban and tumultuous phenomenon than previously theorised.
The current dimensions in the typology of tone are not insightful for understanding the properties of tone in Cushitic languages. Some Cushitic languages are characterised as “pitch-accent” and these cannot be considered stress languages because the criterion of obligatoriness of every word having a stressed unit is not valid for them. In Hyman’s (2006) typology these languages are (restricted) tone languages. Pitch as prominence marker does show stress-like tendencies of culminativity and demarcation in these languages which is why a label pitch-accent has been suggested. The tone properties are better explained by another dimension, namely the fact that the distinctive function of tone hardly plays a role at the lexical level but does play a role at the grammatical level.
Philology. Linguistics, African languages and literature
We study the computational complexity of finite intersections and finite unions of deterministic context-free (dcf) languages. Earlier, Wotschke [J. Comput. System Sci. 16 (1978) 456--461] demonstrated that intersections of $(d+1)$ dcf languages are in general more powerful than intersections of $d$ dcf languages for any positive integer $d$ based on the separation result of the intersection hierarchy of Liu and Weiner [Math. Systems Theory 7 (1973) 185--192]. The argument of Liu and Weiner, however, works only on bounded languages of particular forms, and therefore Wotschke's result is not directly extendable to other non-bounded languages. To deal with a wide range of languages for the non-membership to the intersection hierarchy, we circumvent the specialization of their proof technics and devise a new and practical technical tool: two pumping lemmas for finite unions of dcf languages. Since the family of dcf languages is closed under complementation and also under intersection with regular languages, these pumping lemmas help us establish the non-membership relation of languages formed by finite intersections of target languages. We also concern ourselves with a relationship to deterministic limited automata of Hibbard [Inf. Control 11 (1967) 196--238] in this regard.
Giovanna D'Agostino, Davide Martincigh, Alberto Policriti
Ordering the collection of states of a given automaton starting from an order of the underlying alphabet is a natural move towards a computational treatment of the language accepted by the automaton. Along this path, Wheeler \emph{graphs} have been recently introduced as an extension/adaptation of the Burrows-Wheeler Transform (the now famous BWT, originally defined on strings) to graphs. These graphs constitute an important data-structure for languages, since they allow a very efficient storage mechanism for the transition function of an automaton, while providing a fast support to all sorts of substring queries. This is possible as a consequence of a property -- the so-called \emph{path coherence} -- valid on Wheeler graphs and consisting in an ordering on nodes that "propagates" to (collections of) strings. By looking at a Wheeler graph as an automaton, the ordering on strings corresponds to the co-lexicographic order of the words entering each state. This leads naturally to consider the class of regular languages accepted by Wheeler automata, i.e. the Wheeler languages. It has been shown that, as opposed to the general case, the classic determinization by powerset construction is polynomial on Wheeler languages. As a consequence, most of the classical problems turn out to be "easy" -- that is, solvable in polynomial time -- on Wheeler languages. Moreover, deciding whether a DFA is Wheeler and deciding whether a DFA accepts a Wheeler language is polynomial. Our contribution here is to put an upper bound to easy problems. For instance, whenever we generalize by switching to general NFAs or by not fixing an order of the underlying alphabet, the above mentioned problems become "hard" -- that is NP-complete or even PSPACE-complete.
This article used feminist fat studies as the theoretical rubric through which the author has offered a critical analysis of the representations of fat female characters in the two selected literary texts: Fatropolis (2012) by Tracey L. Thompson and They don’t make plus size spacesuits (2019) by Ali Thompson. Both these texts are set in alternative realities and offer sustained engagements with the ubiquitous and pernicious manifestations of fat phobia in the lives of female characters. Although these authors chose science fiction as a genre, no fat woman would be able to read the texts without wincing in recognition. From the fat phobic micro aggressions to the blatant violence and discrimination that shape daily fat lives, these texts offer our experiences writ large. The fat female body remains something of a blind spot in contemporary feminist studies, which is somewhat strange, considering the profound impact that fat, and the fear of becoming fat, has on the lives of women in almost every sphere of life. Diet culture, which is regarded as the capitalist commodification of fat phobia, is so rife and has become so normalised that most people have simply stopped noticing how their bodies and activities are being policed at both the most intimate and the most public levels of their lives. Diet culture and fat phobia constitute a violent assault on fat women, and the experiences of these characters offer a safe space where feminist scholars could explore the dynamics that function to hurt, minimise and isolate fat women beyond the texts.