Sociogeographic correlates of typological variation in northwestern Bantu gender systems

This paper investigates the sociolinguistic factors that impact the typology and evolution of grammatical gender systems in northwestern Bantu, the most diverse area of the Bantu-speaking world. We base our analyses on a typological classification of 179 northwestern Bantu languages, focusing on various instances of semantic agreement and their role in the erosion of gender marking. In addition, we conduct in-depth analyses of the sociolinguistics and population history of the 17 languages of the sample with the most eroded gender systems. The sociohistorical factors identified to explain these highly eroded systems are then translated into a set of explanatory variables, which we use to conduct extensive quantitative analyses on the 179 language sample. These variables are population size, longitude, latitude, relationship with the Central African rainforest, and border with Ubangi/Central Sudanic languages. All these measures are relevant, with population size and bordering with Ubangi/Central Sudanic being the most robust factors in accounting for the distribution of gender restructuring. We conclude that fine-tuned variable design tailored to language and area-specific ecologies is crucial to the advancement of quantitative sociolinguistic typology.

Predicting Language Performance From Narrative Language Samples

Purpose: Analysis of narrative language samples is a recommended clinical practice in the assessment of children's language skills, but we know little about how results from such analyses relate to overall oral language ability across the early school years. We examined the relations between language sample metrics from a short narrative retell, collected in kindergarten, and an oral language factor in grades kindergarten through 3. Our specific questions were to determine the extent to which metrics from narrative language sample analysis are concurrently related to language in kindergarten and predict language through Grade 3. Method: Participants were a sample of 284 children who were administered a narrative retell task in kindergarten and a battery of vocabulary and grammar measures in kindergarten through Grade 3. Language samples were analyzed for number of different words, mean length of utterance, and a relatively new metric, percent grammatical utterances (PGUs). Structural equation models were used to estimate the concurrent and longitudinal relationships. Results: The narrative language sample metrics were consistently correlated with the individual vocabulary and grammar measures as well as the language factor in each grade, and also consistently and uniquely predicted the language factor in each grade. Standardized path estimates in the structural equation models ranged from 0.20 to 0.39. Conclusions: This study found narrative language sample metrics to be predictive, concurrently and longitudinally, of a latent factor of language from kindergarten through Grade 3. These results further validate the importance of collecting and analyzing narrative language samples, to include PGU along with more traditional metrics, and point to directions for future research. Supplemental Material https://doi.org/10.23641/asha.17700980

Developmental Language Disorder and the Assessment of Spoken Language

Developmental language disorder (DLD), previously known as specific language impairment (SLI), is a long-term developmental disorder affecting approximately 7.5% of children. Language abilities in children with DLD are variable and can be challenging to ascertain with confidence. This chapter aims to discuss some of the challenges associated with assessing the language skills of children with DLD through an overview of different forms of language assessment including standardized language testing, language sample analysis, and observations. Uses and limitations of the different forms of assessment are considered, bearing in mind the different functions of assessment and the need to gain a full understanding of children’s profiles of strength and weakness and communicative functioning in context. The authors conclude with requirements for best practice in assessment and promising avenues of development in this area.

Analysis of Errors Committed by Students in Writing English Essays

Error analysis in linguistics is a systematic process of collecting, identifying, describing, explaining and evaluating unaccepted linguistic forms committed by learners in their writings or speeches. This article attempts to assess the errors committed by 128 bachelor first year education students studying English as a foreign language at Makawanpur Multiple Campus, Hetauda, Nepal in the year 2021. Every student was assigned to write an essay on ‘The Impact of Corona Pandemic on Students’ in about 500 words as the written language sample in a free mode. 128 essays were selected as a sample through the simple random sampling method lottery from 190 essays. All the errors in their essays were identified, described, classified, explained and analyzed. The results revealed that most of the students committed errors in omission at the sentence level, and the causes of the errors were due to intralingual transfer, whereas the highest frequency of errors at the word level was preposition resulted due to mother tongue transfer and overgeneralization.

Taking a Marked Stance through Evaluative Lexical Items: A Study of Selected Features of Obama’s and Trump’s Inaugural Speeches

The paper presents an analysis of Obama’s and Trump’s inaugural addresses with a view to evidencing how language can be manipulated and also reveal the speaker’s political and ideological stance through the use of marked and evaluative lexical items. The language sample selected for analysis contains personal pronouns and possessive adjectives ‘you, your, we, us, our, ours, ourselves, they, their, them, themselves’, determiner ‘other’ and the term ‘America’ with all its derivative forms as used in the two speeches.

A cross-linguistic study of emphatic negative coordination

The purpose of this paper is to provide a detailed cross-linguistic analysis of so-called emphatic negative coordination (enc). This kind of clause linkage is illustrated by neither and nor in She neither could nor would speak lightly of the accident. On the basis of a 250-language sample, the paper lays out a new typology of enc meant to gain novel insights. It is shown that languages can combine enc types, and that contact and borrowing are relevant triggers for the emergence of this sort of clause linkage. The article also reveals that there is considerable variety in the etymological sources and grammaticalization paths of enc markers.

The Index of Productive Syntax: Psychometric Properties and Suggested Modifications

Purpose The Index of Productive Syntax (IPSyn) is a well-known language sample analysis tool. However, its psychometric properties have not been assessed across a wide sample of typically developing preschool-age children and children with language disorders. We sought to determine the profile of IPSyn scores by age over early childhood. We additionally explored whether the IPSyn could be shortened to fewer items without loss of information and whether the required language sample could be shortened from a current required number of 100 utterances to 50. Method We used transcripts from the Child Language Data Exchange System, including 1,051 samples of adult–child conversational play with toys within the theoretical framework of item response theory. Samples included those from typically developing children as well as children with hearing loss, Down syndrome, and late language emergence. Results The Verb Phrase and Sentence Structure subscales showed more stable developmental trajectories over the preschool years and greater differentiation between typical and atypical cohorts than did the Noun Phrase and Question/Negation subscales. A number of current IPSyn scoring items can be dropped without loss of information, and 50-utterance samples demonstrate most of the same psychometric properties of longer samples. Discussion Our findings suggest ways in which the IPSyn can be automated and streamlined (proposed IPSyn-C) so as to provide useful clinical guidance with fewer items and a shorter required language sample. Reference values for the IPSyn-C are provided. Trajectories for one subscale (Question/Negation) appear inherently unstable and may require structured elicitation. Potential limitations, ramifications, and future directions are discussed. Supplemental Material https://doi.org/10.23641/asha.16915690

Language Sample Analysis in Clinical Practice: Speech-Language Pathologists' Barriers, Facilitators, and Needs

Purpose Most speech-language pathologists (SLPs) working with children with developmental language disorder (DLD) do not perform language sample analysis (LSA) on a regular basis, although they do regard LSA as highly informative for goal setting and evaluating grammatical therapy. The primary aim of this study was to identify facilitators, barriers, and needs related to performing LSA by Dutch SLPs working with children with DLD. The secondary aim was to investigate whether a training would change the actual performance of LSA. Method A focus group with 11 SLPs working in Dutch speech-language pathology practices was conducted. Barriers, facilitators, and needs were identified using thematic analysis and categorized using the theoretical domain framework. To address the barriers, a training was developed using software program CLAN. Changes in barriers and use of LSA were evaluated with a survey sent to participants before, directly after, and 3 months posttraining. Results The barriers reported in the focus group were SLPs' lack of knowledge and skills, time investment, negative beliefs about their capabilities, differences in beliefs about their professional role, and no reimbursement from health insurance companies. Posttraining survey results revealed that LSA was not performed more often in daily practice. Using CLAN was not the solution according to participating SLPs. Time investment remained a huge barrier. Conclusions A training in performing LSA did not resolve the time investment barrier experienced by SLPs. User-friendly software, developed in codesign with SLPs might provide a solution. For the short-term, shorter samples, preferably from narrative tasks, should be considered.

Unanalyzable Utterances in Language Sample Analysis Based on the P-LARSP: Preliminary Data of Typical Children Aged 18 - 60 Months

Background: The Persian language assessment, remediation, and screening procedure (P-LARSP) is the first formal approach to the analysis of language samples. Objectives: The present study aimed to investigate the unanalyzable utterances and mean length of utterances (MLUs: morpheme/analyzable text units) based on the first two sections of the P-LARSP. Methods: Experienced speech and language pathologists (SLPs) collected and analyzed the 10-minute language samples from 96 typical children aged 18 - 60 months within the context of free play. The unanalyzable units included unintelligible utterances, symbolic noise, deviant, incomplete, ambiguous, and stereotyped units, repetition, and structurally abnormal text units. Results: No significant differences were observed between the age groups in terms of the total number of the text units (P > 0.05) and unanalyzable text units (P = 0.08). Analyzable text units (P = 0.008) and MLUs (P = 0.004) were significant across the age groups. In addition, each category of the unanalyzable text units had a specific pattern, and the percentage of the incomplete utterances increased significantly from 18 to 60 months of age (P = 0.002). Conclusions: By applying the first two sections of the P-LARSP, we could sieve the analyzable from the unanalyzable text units and demonstrate the increasing trend of MLUs across the age groups. Increased incomplete utterances with age should be considered by SLPs during intervention and evaluation.

Bayesian Generalized Linear Mixed-Model Analysis of Language Samples: Detecting Patterns in Expository and Narrative Discourse of Adolescents With Traumatic Brain Injury

Purpose Generalized linear mixed-model (GLMM) and Bayesian methods together provide a framework capable of handling a wide variety of complex data commonly encountered across the communication sciences. Using language sample analysis, we demonstrate the utility of these methods in answering specific questions regarding the differences between discourse patterns of children who have experienced a traumatic brain injury (TBI), as compared to those with typical development. Method Language samples were collected from 55 adolescents ages 13–18 years, five of whom had experienced a TBI. We describe parameters relating to the productivity, syntactic complexity, and lexical diversity of language samples. A Bayesian GLMM is developed for each parameter of interest, relating these parameters to age, sex, prior history (TBI or typical development), and socioeconomic status, as well as the type of discourse sample (compare–contrast, cause–effect, or narrative). Statistical models are thoroughly described. Results Comparing the discourse of adolescents with TBI to those with typical development, substantial differences are detected in productivity and lexical diversity, while differences in syntactic complexity are more moderate. Female adolescents exhibited greater syntactic complexity, while male adolescents exhibited greater productivity and lexical diversity. Generally, our models suggest more advanced discourse among adolescents who are older or who have indicators of higher socioeconomic status. Differences relating to lecture type were also detected. Conclusions Bayesian and GLMM methods yield more informative and intuitive results than traditional statistical analyses, with a greater degree of confidence in model assumptions. We recommend that these methods be used more widely in language sample analysis. Supplemental Material https://doi.org/10.23641/asha.14226959