A call for linguistic and culturally congruent family-centred early hearing detection and intervention programmes in South Africa.

Early Hearing Detection and Intervention (EHDI) programmes are recognised as the standard of care for newborns and infants presenting with hearing impairment, globally. However, widespread implementation of these programmes is far from being realised and faces numerous challenges within the South African context. The United Nations' sustainable development goal 3.8 and South Africa's national development plan seek to achieve equitable access to healthcare service, including EHDI. However, healthcare access is a complex concept which encompasses the dimensions: availability, affordability, acceptability and accommodation in healthcare. South Africa has made great progress towards universal implementation of EHDI programmes. Despite this progress, availability and affordability of these programmes are limited and their acceptability has received limited research focus in this context. Furthermore, accommodation of caregivers, as co-drivers of EHDI programmes and ensuring that EHDI programmes are linguistically and culturally congruent have also been overlooked within the South African context.Contribution: Increased robust efforts in improving access through availability and affordability of EHDI programmes are warranted in South Africa. However, improving access to these programmes through availability and affordability initiatives alone will not result in a pragmatic improvement in their accessibility. Acceptability of these programmes and accommodations such as involving caregivers and family members of children with hearing impairment as equal partners in EHDI programmes and being cognisant of their linguistic and cultural needs must be considered.

Perception of vocoded speech in domestic dogs.

Humans have an impressive ability to comprehend signal-degraded speech; however, the extent to which comprehension of degraded speech relies on human-specific features of speech perception vs. more general cognitive processes is unknown. Since dogs live alongside humans and regularly hear speech, they can be used as a model to differentiate between these possibilities. One often-studied type of degraded speech is noise-vocoded speech (sometimes thought of as cochlear-implant-simulation speech). Noise-vocoded speech is made by dividing the speech signal into frequency bands (channels), identifying the amplitude envelope of each individual band, and then using these envelopes to modulate bands of noise centered over the same frequency regions - the result is a signal with preserved temporal cues, but vastly reduced frequency information. Here, we tested dogs' recognition of familiar words produced in 16-channel vocoded speech. In the first study, dogs heard their names and unfamiliar dogs' names (foils) in vocoded speech as well as natural speech. In the second study, dogs heard 16-channel vocoded speech only. Dogs listened longer to their vocoded name than vocoded foils in both experiments, showing that they can comprehend a 16-channel vocoded version of their name without prior exposure to vocoded speech, and without immediate exposure to the natural-speech version of their name. Dogs' name recognition in the second study was mediated by the number of phonemes in the dogs' name, suggesting that phonological context plays a role in degraded speech comprehension.

Linguistic based emotion analysis using softmax over time attention mechanism.

Recognizing the real emotion of humans is considered the most essential task for any customer feedback or medical applications. There are many methods available to recognize the type of emotion from speech signal by extracting frequency, pitch, and other dominant features. These features are used to train various models to auto-detect various human emotions. We cannot completely rely on the features of speech signals to detect the emotion, for instance, a customer is angry but still, he is speaking at a low voice (frequency components) which will eventually lead to wrong predictions. Even a video-based emotion detection system can be fooled by false facial expressions for various emotions. To rectify this issue, we need to make a parallel model that will train on textual data and make predictions based on the words present in the text. The model will then classify the type of emotions using more comprehensive information, thus making it a more robust model. To address this issue, we have tested four text-based classification models to classify the emotions of a customer. We examined the text-based models and compared their results which showed that the modified Encoder decoder model with attention mechanism trained on textual data achieved an accuracy of 93.5%. This research highlights the pressing need for more robust emotion recognition systems and underscores the potential of transfer models with attention mechanisms to significantly improve feedback management processes and the medical applications.

Spontaneous perspective-taking in real-time language comprehension: evidence from eye-movements and grain of coordination.

Linguistic communication requires interlocutors to consider differences in each other's knowledge (perspective-taking). However, perspective-taking might either be spontaneous or strategic. We monitored listeners' eye movements in a referential communication task. A virtual speaker gave temporally ambiguous instructions with scalar adjectives ("big" in "big cubic block"). Scalar adjectives assume a contrasting object (a small cubic block). We manipulated whether the contrasting object (a small triangle) for a competitor object (a big triangle) was in common ground (visible to both speaker and listener) or was occluded so it was in the listener's privileged ground, in which case perspective-taking would allow earlier reference-resolution. We used a complex visual context with multiple objects, making strategic perspective-taking unlikely when all objects are in the listener's referential domain. A turn-taking, puzzle-solving task manipulated whether participants could anticipate a more restricted referential domain. Pieces were either confined to a small area (requiring fine-grained coordination) or distributed across spatially distinct regions (requiring only coarse-grained coordination). Results strongly supported spontaneous perspective-taking: Although comprehension was less time-locked in the coarse-grained condition, participants in both conditions used perspective information to identify the target referent earlier when the competitor contrast was in privileged ground, even when participants believed instructions were computer-generated.

Risk assessment of deep-sea floating offshore wind power projects based on hesitant fuzzy linguistic term set considering trust relationship among experts.

The development of deep-sea floating offshore wind power (FOWP) is the key to fully utilizing water resources to enhance wind resources in the years ahead, and then the project is still in its initial stage, and identifying risks is a crucial step before promoting a significant undertaking. This paper proposes a framework for identifying risks in deep-sea FOWP projects. First, this paper identifies 16 risk criteria and divides them into 5 groups to establish a criteria system. Second, hesitant fuzzy linguistic term set (HFLTS) and triangular fuzzy number (TFN) are utilized to gather and describe the criterion data to ensure the robustness and completeness of the criterion data. Third, extending the method for removal effects of criteria (MEREC) to the HFLTS environment through the conversion of TFNs, under the influence of subjective preference and objective fairness, a weighting method combining analytic network process (ANP) and MEREC is utilized to calculate criteria weights, and the trust relationship and consistency between experts are used to calculate the expert weights to avoid the subjective weighting given by experts arbitrariness. Fourth, the study's findings indicated that the overall risk level of the deep-sea FOWP projects is "medium." Fifth, sensitivity and comparative analyses were conducted to test the reliability of the assessment outcomes. lastly, this research proposes risk management measures for the deep-sea FOWP project's establishment from economic, policy, technology, environment, and management aspects.

Does Pollyanna hypothesis hold true in death narratives? A sentiment analysis approach.

Pollyanna hypothesis claims that human beings have a universal tendency to use positive words more frequently and broadly than negative words. The present study aims to test Pollyanna hypothesis in medical death narratives at both lexical and text levels by using sentiment analysis and emotion detection methods, and to qualitatively analyze the contextual use of emotion words to deepen the understanding of doctors' emotions. Sentiment analysis showed a strong token-based linguistic positivity and a weak type-based negativity bias at the lexical level, and a general positivity bias at the text level, despite the gender of the doctors. Emotion detection discovered three prominent emotions of "joy", "sadness", and "anger", and a greater diversity of negative emotions in contrast to positive emotions in medical death narratives. Contextual analysis revealed that emotion words associated with joy were primarily observed in contexts related to doctors' actions and behaviors aiming to benefit others and promote social wellbeing. Emotion words associated with sadness and anger were chiefly employed to describe situations involving patients' death and doctors' attitudes towards death. The results confirm Pollyanna hypothesis at both token-based lexical level and text level and falsify the hypothesis at type-based lexical level. Possible explanations are explored by contextual analysis, and theoretical analysis from the perspectives of cognitive linguistics and social psychology. The findings are expected to enrich the understanding of Pollyanna hypothesis as well as the junior doctors' emotional responses to clinical deaths.

Dysphagia Service Delivery in the Educational Setting: Pediatric Feeding Disorder and the Culturally Responsive Clinician.

PURPOSE: This article addresses considerations for the speech-language pathologist to ensure culturally competent dysphagia management in the school setting for children with oral motor, swallowing, and pediatric feeding disorders (PFDs). There is also discussion of the multifactorial cultural and linguistic influences that impact collaborative educational decisions when establishing and implementing school-based dysphagia services. CONCLUSIONS: The consideration of cultural and linguistic factors for the child with oral motor, swallowing, and/or PFDs is essential when diagnosing, treating, and planning for dysphagia service delivery. By recognizing and including culturally appropriate interventions and recommendations, speech-language pathologists enhance opportunities for positive outcomes and treatment efficacy when providing pediatric dysphagia services in the educational setting for children from culturally and linguistically diverse backgrounds.

Mental rotation and language in autism spectrum disorder.

Though visuospatial skills are often considered a relative strength in autism spectrum disorder (ASD), unexplained difficulties relative to neurotypical (NT) peers have also been observed. Dissociations between spatial cognition and language skills in ASD may explain these difficulties given that these systems are linked in NT individuals. The current study examined performance on a mental rotation task that systematically varied stimulus features and the degree to which performance was associated with language in ASD relative to NT peers. Participants were children and young adults with ASD and 25 pairwise age- and IQ-matched NT peers (p's>0.53). The mental rotation task involved four conditions: two-dimensional (2D) abstract figures, three-dimensional (3D) abstract figures, 2D common objects, and 3D common objects. Structural language was measured using the grammar subscale from the Test of Language Development: Intermediate adapted for Norwegian. Mixed-effects model results indicated that autistic individuals were less accurate and had slower reaction time across mental rotation task conditions than NT peers. Language was associated with mental rotation accuracy for both groups across conditions, but with reaction time only for the NT group. The current study demonstrated selective associations between language and performance on a classic spatial cognition task in autistic individuals. Namely, there was a dissociation between language and in-the-moment efficiency in the ASD group, and this dissociation may reflect a broader dissociation between visuospatial and language systems.

Resilience evaluation of low-carbon supply chain based on improved matter-element extension model.

How to evaluate the resilience level and change trend of supply chain is an important research direction in current supply chain management practice. This paper proposes a new method of supply chain resilience assessment based on hesitant fuzzy linguistic term set (HFLTS) and matter element extension theory. Firstly, based on the research status quo at home and abroad, a low-carbon enterprise supply chain resilience assessment index system is established, which includes six first-level indicators and corresponding 21 second-level indicators of product supply resilience, resource resilience, partner resilience, information response resilience, financial resilience and knowledge resilience. Secondly, HFLTS was used to collect expert opinions and Ordered Weighted Arithmetic (OWA) to calculate the expert composite language, by which the fuzzy evaluation matrix of supply chain resilience assessment indicators was obtained. Once again, the resilience indicator weights are determined based on a game-theoretic portfolio assignment method combining the best-worst method (BWM) and the CRITIC method. Finally, the nearness degree function is combined with the extension comprehensive evaluation method to improve the matter element extension model, and the supply chain resilience assessment model of low-carbon enterprises based on the game theory combination assignment-improved matter element extension is established. Taking X low-carbon enterprise as an example, the evaluation results show that the supply chain resilience level of this enterprise is II, and the eigenvalue of the grade variable is 2.69, and the supply chain resilience is shifting to III, and the supply chain resilience is shifting to III, which indicates that the supply chain resilience of this enterprise is being enhanced. Therefore, the improved matter element extension not only ensures the accuracy of the evaluation results, but also has higher prediction accuracy.

The Importance of Linguistic Factors: He Likes Subject Referents.

We report the results of one visual-world eye-tracking experiment and two referent selection tasks in which we investigated the effects of information structure in the form of prosody and word order manipulation on the processing of subject pronouns er and der in German. Factors such as subjecthood, focus, and topicality, as well as order of mention have been linked to an increased probability of certain referents being selected as the pronoun's antecedent and described as increasing this referent's prominence, salience, or accessibility. The goal of this study was to find out whether pronoun processing is primarily guided by linguistic factors (e.g., grammatical role) or nonlinguistic factors (e.g., first-mention), and whether pronoun interpretation can be described in terms of referents' "prominence" / "accessibility" / "salience." The results showed an overall subject preference for er, whereas der was affected by the object role and focus marking. While focus increases the attentional load and enhances memory representation for the focused referent making the focused referent more available, ultimately it did not affect the final interpretation of er, suggesting that "prominence" or the related concepts do not explain referent selection preferences. Overall, the results suggest a primacy of linguistic factors in determining pronoun resolution.

Effects of mobility on dialect change: Introducing the linguistic mobility index.

Increased geographical mobility prompts dialectologists to factor in survey participants' exposure to linguistic variation in their research. Changing mobility patterns (e.g. longer-distance commuting; easier relocation to distant places for work, study or marriage) have caused linguistic connections to become much more diverse, potentially contributing to the acceleration of dialect change. In this methodological work we propose the Linguistic Mobility Index (LMI) to estimate long-term exposure to dialectal variation and thereby to provide a reference of "localness" about survey participants. Based on data about a survey participant's linguistic biography, an LMI may comprise combinations of influential agents and environments, such as the dialects of parents and long-term partners, the places where participants have lived and worked, and the participants' level of education. We encapsulate the linguistic effects of these agents based on linguistic differences, the intensity and importance of the relationship. We quantify the linguistic effects in three steps. 1) The linguistic effect of an agent is represented by a linguistic distance, 2) This linguistic distance is weighted based on the intensity of the participant's exposure to the agent, and 3) Further weighted according to the relationship embodied by the agent. LMI is conceptualised and evaluated based on 500 speakers from 125 localities in the Swiss German Dialects Across Time and Space (SDATS) corpus, and guidance is provided for establishing LMI in other linguistic studies. For the assessment of LMI's applicability to other studies, four LMI prototypes are constructed based on the SDATS corpus, employing different theoretical considerations and combinations of influential agents and environments to simulate the availability of biographical data in other studies. Using mixed-effects modelling, we evaluate the utility of the LMI prototypes as predictors of dialect change between historic and contemporary linguistic data of Swiss German. The LMI prototypes successfully show that higher exposure to dialectal variation contributes to more dialect change and that its effect is stronger than some sociodemographic variables that are often tested for affecting dialect change (e.g. sex and educational background).

Linguistic correlates of societal variation: A quantitative analysis.

Traditionally, many researchers have supported a uniformitarian view whereby all languages are of roughly equal complexity, facilitated by internal trade-offs between complexity at different levels, such as morphology and syntax. The extent to which the speakers' societies influence the trade-offs has not been well studied. In this paper, we focus on morphology and syntax, and report significant correlations between specific linguistic and societal features, in particular those relating to exoteric (open) vs. esoteric (close-knit) society types, characterizable in terms of population size, mobility, communication across distances, etc. We conduct an exhaustive quantitative analysis drawing upon WALS, D-Place, Ethnologue and Glottolog, finding some support for our hypothesis that languages spoken by exoteric societies tend towards more complex syntaxes, while languages spoken by esoteric societies tend towards more complex morphologies.

Language-like efficiency and structure in house finch song.

Communication needs to be complex enough to be functional while minimizing learning and production costs. Recent work suggests that the vocalizations and gestures of some songbirds, cetaceans and great apes may conform to linguistic laws that reflect this trade-off between efficiency and complexity. In studies of non-human communication, though, clustering signals into types cannot be done a priori, and decisions about the appropriate grain of analysis may affect statistical signals in the data. The aim of this study was to assess the evidence for language-like efficiency and structure in house finch (Haemorhous mexicanus) song across three levels of granularity in syllable clustering. The results show strong evidence for Zipf's rank-frequency law, Zipf's law of abbreviation and Menzerath's law. Additional analyses show that house finch songs have small-world structure, thought to reflect systematic structure in syntax, and the mutual information decay of sequences is consistent with a combination of Markovian and hierarchical processes. These statistical patterns are robust across three levels of granularity in syllable clustering, pointing to a limited form of scale invariance. In sum, it appears that house finch song has been shaped by pressure for efficiency, possibly to offset the costs of female preferences for complexity.

Limited but specific engagement of the mature language network during linguistic statistical learning.

Statistical learning (SL) is the ability to detect and learn regularities from input and is foundational to language acquisition. Despite the dominant role of SL as a theoretical construct for language development, there is a lack of direct evidence supporting the shared neural substrates underlying language processing and SL. It is also not clear whether the similarities, if any, are related to linguistic processing, or statistical regularities in general. The current study tests whether the brain regions involved in natural language processing are similarly recruited during auditory, linguistic SL. Twenty-two adults performed an auditory linguistic SL task, an auditory nonlinguistic SL task, and a passive story listening task as their neural activation was monitored. Within the language network, the left posterior temporal gyrus showed sensitivity to embedded speech regularities during auditory, linguistic SL, but not auditory, nonlinguistic SL. Using a multivoxel pattern similarity analysis, we uncovered similarities between the neural representation of auditory, linguistic SL, and language processing within the left posterior temporal gyrus. No other brain regions showed similarities between linguistic SL and language comprehension, suggesting that a shared neurocomputational process for auditory SL and natural language processing within the left posterior temporal gyrus is specific to linguistic stimuli.

Responses of Five Different Artificial Intelligence Chatbots to the Top Searched Queries About Erectile Dysfunction: A Comparative Analysis.

The aim of the study is to evaluate and compare the quality and readability of responses generated by five different artificial intelligence (AI) chatbots-ChatGPT, Bard, Bing, Ernie, and Copilot-to the top searched queries of erectile dysfunction (ED). Google Trends was used to identify ED-related relevant phrases. Each AI chatbot received a specific sequence of 25 frequently searched terms as input. Responses were evaluated using DISCERN, Ensuring Quality Information for Patients (EQIP), and Flesch-Kincaid Grade Level (FKGL) and Reading Ease (FKRE) metrics. The top three most frequently searched phrases were "erectile dysfunction cause", "how to erectile dysfunction," and "erectile dysfunction treatment." Zimbabwe, Zambia, and Ghana exhibited the highest level of interest in ED. None of the AI chatbots achieved the necessary degree of readability. However, Bard exhibited significantly higher FKRE and FKGL ratings (p = 0.001), and Copilot achieved better EQIP and DISCERN ratings than the other chatbots (p = 0.001). Bard exhibited the simplest linguistic framework and posed the least challenge in terms of readability and comprehension, and Copilot's text quality on ED was superior to the other chatbots. As new chatbots are introduced, their understandability and text quality increase, providing better guidance to patients.

Large Language Models: A Historical and Sociocultural Perspective.

This letter explores the intricate historical and contemporary links between large language models (LLMs) and cognitive science through the lens of information theory, statistical language models, and socioanthropological linguistic theories. The emergence of LLMs highlights the enduring significance of information-based and statistical learning theories in understanding human communication. These theories, initially proposed in the mid-20th century, offered a visionary framework for integrating computational science, social sciences, and humanities, which nonetheless was not fully fulfilled at that time. The subsequent development of sociolinguistics and linguistic anthropology, especially since the 1970s, provided critical perspectives and empirical methods that both challenged and enriched this framework. This letter proposes that two pivotal concepts derived from this development, metapragmatic function and indexicality, offer a fruitful theoretical perspective for integrating the semantic, textual, and pragmatic, contextual dimensions of communication, an amalgamation that contemporary LLMs have yet to fully achieve. The author believes that contemporary cognitive science is at a crucial crossroads, where fostering interdisciplinary dialogues among computational linguistics, social linguistics and linguistic anthropology, and cognitive and social psychology is in particular imperative. Such collaboration is vital to bridge the computational, cognitive, and sociocultural aspects of human communication and human-AI interaction, especially in the era of large language and multimodal models and human-centric Artificial Intelligence (AI).

Sustainability evaluation of sports tourism using a linguistic neutrosophic multi-criteria decision-making method.

Sports tourism represents a novel industrial manifestation of the profound integration between the tourism and sports sectors. The objective of this research is to examine an innovative multi-criteria decision-making (MCDM) method for the sustainability evaluation of sports tourism. The largest innovations are the expression and treatment of ambiguous data and interdependent evaluation criteria in the sports tourism sustainability evaluation process. On the one hand, intricate assessment data is represented using linguistic neutrosophic numbers (LNNs), which employ three linguistic variables to convey uncertainty and imprecision. On the other hand, to effectively capture the interrelationships among inputs, two novel aggregation operators are proposed. They are devised based on the Einstein operations and Heronian mean operators of LNNs. Subsequently, a linguistic neutrosophic evaluation method utilizing the aforementioned operators is presented. Comparative and sensitivity analyses conclude that great interdependence exists among five different dimensions of sustainability evaluation in sports tourism, and the proposed method can reflect the interrelations among inputs without redundant calculations.

High-level language brain regions process sublexical regularities.

A network of left frontal and temporal brain regions supports language processing. This "core" language network stores our knowledge of words and constructions as well as constraints on how those combine to form sentences. However, our linguistic knowledge additionally includes information about phonemes and how they combine to form phonemic clusters, syllables, and words. Are phoneme combinatorics also represented in these language regions? Across five functional magnetic resonance imaging experiments, we investigated the sensitivity of high-level language processing brain regions to sublexical linguistic regularities by examining responses to diverse nonwords-sequences of phonemes that do not constitute real words (e.g. punes, silory, flope). We establish robust responses in the language network to visually (experiment 1a, n = 605) and auditorily (experiments 1b, n = 12, and 1c, n = 13) presented nonwords. In experiment 2 (n = 16), we find stronger responses to nonwords that are more well-formed, i.e. obey the phoneme-combinatorial constraints of English. Finally, in experiment 3 (n = 14), we provide suggestive evidence that the responses in experiments 1 and 2 are not due to the activation of real words that share some phonology with the nonwords. The results suggest that sublexical regularities are stored and processed within the same fronto-temporal network that supports lexical and syntactic processes.

Promoting leisure functions through setting creative linguistic landscapes in recreational zones.

Using creativity to promote recreational services is crucial. Accordingly, creative linguistic landscapes (CLLs) are being used to improve visitors' experiences in some recreational zones. However, relevant research is still in its early stages. Therefore, this study was conducted. It summarized the leisure function categories and function evaluation indicators of CLLs in recreational zones respectively based on image materials and related online reviews. The leisure function outcomes of all CLL types were ranked using the fuzzy PROMETHEE method; based on this ranking, a CLL configuration optimization mode was suggested. The findings reveal the following. (1) Currently, there are mainly nine leisure function types of CLL in practice, although the type structure is severely imbalanced; there are 12 primary corresponding function evaluation indicators, although each of them draws significantly different attention. (2) There are notable variations among the outcomes of different types of functions of CLL: mood adjustment is the most advantageous function of CLL for leisure services, followed by emotional guidance and cognitive building functions; (3) According to the study findings, in the configuration of CLL, which aims at leisure function optimization, the "function focusing and coordinating mode (the superior functions of CLL are focused on and its various functions are coordinated)" should be adopted. The results provide meaningful lessons for the establishment of rational and effective CLL in recreational zones.

What's in a Name? Experimental Evidence of Gender Bias in Recommendation Letters Generated by ChatGPT.

BACKGROUND: Artificial intelligence chatbots such as ChatGPT (OpenAI) have garnered excitement about their potential for delegating writing tasks ordinarily performed by humans. Many of these tasks (eg, writing recommendation letters) have social and professional ramifications, making the potential social biases in ChatGPT's underlying language model a serious concern. OBJECTIVE: Three preregistered studies used the text analysis program Linguistic Inquiry and Word Count to investigate gender bias in recommendation letters written by ChatGPT in human-use sessions (N=1400 total letters). METHODS: We conducted analyses using 22 existing Linguistic Inquiry and Word Count dictionaries, as well as 6 newly created dictionaries based on systematic reviews of gender bias in recommendation letters, to compare recommendation letters generated for the 200 most historically popular "male" and "female" names in the United States. Study 1 used 3 different letter-writing prompts intended to accentuate professional accomplishments associated with male stereotypes, female stereotypes, or neither. Study 2 examined whether lengthening each of the 3 prompts while holding the between-prompt word count constant modified the extent of bias. Study 3 examined the variability within letters generated for the same name and prompts. We hypothesized that when prompted with gender-stereotyped professional accomplishments, ChatGPT would evidence gender-based language differences replicating those found in systematic reviews of human-written recommendation letters (eg, more affiliative, social, and communal language for female names; more agentic and skill-based language for male names). RESULTS: Significant differences in language between letters generated for female versus male names were observed across all prompts, including the prompt hypothesized to be neutral, and across nearly all language categories tested. Historically female names received significantly more social referents (5/6, 83% of prompts), communal or doubt-raising language (4/6, 67% of prompts), personal pronouns (4/6, 67% of prompts), and clout language (5/6, 83% of prompts). Contradicting the study hypotheses, some gender differences (eg, achievement language and agentic language) were significant in both the hypothesized and nonhypothesized directions, depending on the prompt. Heteroscedasticity between male and female names was observed in multiple linguistic categories, with greater variance for historically female names than for historically male names. CONCLUSIONS: ChatGPT reproduces many gender-based language biases that have been reliably identified in investigations of human-written reference letters, although these differences vary across prompts and language categories. Caution should be taken when using ChatGPT for tasks that have social consequences, such as reference letter writing. The methods developed in this study may be useful for ongoing bias testing among progressive generations of chatbots across a range of real-world scenarios. TRIAL REGISTRATION: OSF Registries osf.io/ztv96; https://osf.io/ztv96.