This paper revisits the relationship between tax evasion and tax rates in a heterogeneous-agent, incomplete-markets model. Extending the foundational works of Allingham and Sandmo (1972) and Yitzhaki (1974), we explore how financially constrained households use tax evasion to mitigate the adverse effects of market imperfections. We show that deterrence policies, such as audit probabilities and penalties, exacerbate the effects of borrowing constraints. Importantly, increasing income tax rates can sometimes alleviate these negative impacts when individuals evade taxes. We identify three mechanisms shaping underreporting: the direct effect, the threshold effect, and the income effect. These help explain when and why the Yitzhaki puzzle arises. Numerical results reveal a non-monotonic relationship between tax rates and underreporting, underscoring the relative strength of these effects and offering fresh insights into the Yitzhaki puzzle.

This article considers a general class of varying coefficient models defined by a set of moment equalities and/or inequalities, where unknown functional parameters are not necessarily point-identified. We propose an inferential procedure for a subvector of the varying parameters and establish the asymptotic validity of the resulting confidence sets uniformly over a broad family of data-generating processes. We also propose a practical specification test for a set of necessary conditions of our model. Monte Carlo studies show that the proposed methods have good finite sample properties. We apply our method to estimate the return to education in China using its 1%-population census data from 2005.

Aims: The Early Intervention in Psychosis (EPIP) team in Singapore extended its remit to see 12–15-year-old patients presenting with diagnosed psychosis (not ARMS) in 2019. This program has been running for 4 years and a sizeable data set is now available on this group of patients. This is a novel service. Research and evaluation of this service will add to the understanding of how to configure services for this clinically challenging population.

Methods: De-identified operational data is available at the Institute of Mental Health. Data from 2019–2022 was extracted with the permission of the Data Protection Officer and de-identified through the Data Science Office. Patients aged 12–18 seen by EPIP from 2019–2021 were included in the study. This will allow 1 year’s data to be included and studied. Descriptive statistics looking at the demographics, orders, chargeable contact points with the hospital, admissions and payment information are described for this group.

Results: 78 patients were found from this dataset to have been included in the 12–18 EPIP program. In the 3 years 2019–2021, there were gradually increasing numbers of patients seen in this program, 21, 25 and 32 respectively. There were similar numbers of patients in the 12–15 age group as compared with those accepted into the service between 16–18. There was a higher representation of ethnic minorities and females into the program.

Conclusion: This is a new service looking at confirmed cases of psychosis in the younger age group 12–15. As an estimate, this figure is similar to the number of patients accepted to Early psychosis intervention programs aged 16–18. There is an over representation of females and ethnic minorities in this clinical population. There is a distinct need for services targeting this group of patients.

The effort required for analysis of operational data is high and dependent on the quality of the operation data repository. The current state of the data sets in IMH are not conducive for studying and may limit the reliability of the data presented here. Knowledge of the dataset and its clinical implications was required to be able to process the data. Further exploration of this data is planned.

This investigation examines the dynamic response of an accelerating turbulent pipe flow using direct numerical simulation data sets. A low/high-pass Fourier filter is used to investigate the contribution and time dependence of the large-scale motions (LSM) and the small-scale motions (SSM) into the transient Reynolds shear stress. Additionally, it analyses how the LSM and SSM influence the mean wall shear stress using the Fukagata–Iwamoto–Kasagi identity. The results reveal that turbulence is frozen during the early flow excursion. During the pretransition stage, energy growth of the LSM and a subtle decay in the SSM is observed, suggesting a laminarescent trend of SSM. The transition period exhibits rapid energy growth in the SSM energy spectrum at the near-wall region, implying a shift in the dominant contribution from LSM to SSM to the frictional drag. The core-relaxation stage shows a quasisteady behaviour in large- and small-scale turbulence at the near-wall region and progressive growth of small- and large-scale turbulence within the wake region. The wall-normal gradient of the Reynolds shear stress premultiplied energy cospectra was analysed to understand how LSM and SSM influence the mean momentum balance across the different transient stages. A relevant observation is the creation of a momentum sink produced at the buffer region in large- and very large-scale (VLSM) wavelengths during the pretransition. This sink region annihilates a momentum source located in the VLSM spectrum and at the onset of the logarithmic region of the net-force spectra. This region is a source term in steady wall-bounded turbulence.

This review on English language teaching (ELT) in Singapore examines 159 empirical research studies published between 2017 and 2023 in both internationally recognised peer-reviewed journals and less well-known regional journals. With this comprehensive review, we aim to raise awareness of ELT research in Singapore for international, regional, and local readership. This will also serve as a starting point for educators, scholars, and researchers to investigate ELT in Singapore. The review yielded five themes: teaching the language skills; multiliteracies and technology; bi/multilingualism/bidialectalism and English; English as an academic language; and teacher education for ELT. While there is continuity from the last two reviews of research from Singapore in 2009 and 2021, reflected in the single theme of teaching language skills, the other themes represent new directions.

Objectives/Goals: We assessed the feasibility of using a large language model (LLM) to create lay language descriptions of study protocols for recruitment, which has the potential to improve accessibility and transparency of clinical studies and enable participants to make informed decisions. Methods/Study Population: All studies from a clinical research recruitment platform were included, which features human-written lay descriptions and titles for study recruitment. Corresponding protocol summaries in the IRB system were extracted and translated into lay language using a LLM (gpt-35-turbo-0613). A subset was used to develop prompt variations through an iterative process. Prompt strategies evaluated include chain-of-thought and few-shot prompting techniques. LLM-generated and human-written descriptions were compared for readability using Flesch–Kincaid and Simple Measure of Gobbledygook (SMOG) reading grade levels and information completeness using Word Movers’ Distance (WMD). Results/Anticipated Results: A total of 55 study descriptions were included – 10 were used to develop prompts and 45 were used for evaluation. The final LLM instructions included multistep prompts. The LLM was first instructed to produce a two- to three-sentence long description without using scientific jargon and included two pairs of examples. The LLM was then asked to shorten the description and finally to provide an engaging title. LLM-generated and human-written summaries were similar in length (median (IQR) 328 (278.5–360.5) vs. 342 (203–532.5) characters, respectively). LLM-generated summaries had lower Flesch-Kincaid grade level (5.15 vs. 8.28, p Discussion/Significance of Impact: An LLM can be used to generate lay language summaries that are readable at a lower grade level while maintaining semantic similarity. This approach can be used to improve the drafting of summaries for recruitment, thereby improving accessibility to potential participants. Future work includes human evaluation and implementation into practice.

The attitudes toward genomics and precision medicine (AGPM) measure examines attitudes toward activities such as genetic testing, gene editing, and biobanking. This is a useful tool for research on the ethical, legal, and social implications of genomics, a major program within the National Institutes of Health. We updated the AGPM to explore controversies over mRNA vaccines. This brief report examines the factor structure of the updated AGPM using a sample of 4939 adults in the USA. The updated AGPM’s seven factors include health benefits, knowledge benefits, and concerns about the sacredness of life, privacy, gene editing, mRNA vaccines, and social justice.

Chiu Chin-po, or Chō Chin-bo (周金波) as he was known in Japan, was born in Keelung, Taiwan, in January 1920—twenty-five years after Japan acquired the island as a result of the Sino-Japanese War, 1894-1895. His mother took him to Tokyo when he was three, in 1923, to join her husband who was studying dentistry at Nihon University. In September that year, Tokyo was hit by the Great Kanto Earthquake that killed 100,000 people. The Chiu family was among those affected, and returned to Taiwan. Chiu attended “public school,” the elementary school for Taiwanese children, in Keelung and a few other cities. He recalled being bullied because he did not understand Taiwanese.

In this paper, we apply sequential one-sided confidence interval estimation procedures with β-protection to adaptive mastery testing. The procedures of fixed-width and fixed proportional accuracy confidence interval estimation can be viewed as extensions of one-sided confidence interval procedures. It can be shown that the adaptive mastery testing procedure based on a one-sided confidence interval with β-protection is more efficient in terms of test length than a testing procedure based on a two-sided/fixed-width confidence interval. Some simulation studies applying the one-sided confidence interval procedure and its extensions mentioned above to adaptive mastery testing are conducted. For the purpose of comparison, we also have a numerical study of adaptive mastery testing based on Wald's sequential probability ratio test. The comparison of their performances is based on the correct classification probability, averages of test length, as well as the width of the “indifference regions.” From these empirical results, we found that applying the one-sided confidence interval procedure to adaptive mastery testing is very promising.

Item calibration is an essential issue in modern item response theory based psychological or educational testing. Due to the popularity of computerized adaptive testing, methods to efficiently calibrate new items have become more important than that in the time when paper and pencil test administration is the norm. There are many calibration processes being proposed and discussed from both theoretical and practical perspectives. Among them, the online calibration may be one of the most cost effective processes. In this paper, under a variable length computerized adaptive testing scenario, we integrate the methods of adaptive design, sequential estimation, and measurement error models to solve online item calibration problems. The proposed sequential estimate of item parameters is shown to be strongly consistent and asymptotically normally distributed with a prechosen accuracy. Numerical results show that the proposed method is very promising in terms of both estimation accuracy and efficiency. The results of using calibrated items to estimate the latent trait levels are also reported.

Exclusion of evidence when its probative value is exceeded by its risk of creating unfair prejudice has long been a fundamental safeguard against unfair trials and wrongful convictions. In 2016, IMM v The Queen (IMM) curtailed that safeguard by holding that trial judges should assess probative value on the assumption that the evidence is reliable and credible. The IMM majority placed emphasis on the capacity of the evidence. In doing so, it provided a mysterious qualification: some evidence may lack probative value not because it is unreliable, but because it is ‘simply unconvincing’. The majority illustrated unconvincingness with the example of an unreliable eyewitness identification. Courts and legal scholars criticised the majority judgment for its harmful implications and for its apparent incoherence. From a review of almost 4 years of post-IMM jurisprudence and deeper exploration into one particular case, we find that ‘simply unconvincing’ has accentuated the confusion and inconsistency in Australian evidence jurisprudence.