The international education sector is Australia’s largest service-based export industry, making a significant contribution to our economy. International students also provide valuable labour during their stay in Australia and many become skilled migrants post-graduation. However, the current student visa conditions that limit international students’ capacity to undertake work are also inhibiting their successful transition into graduate employment and their ability to secure permanent residency. They are required to navigate contradictions between the restriction on the number of hours of work they can undertake as an international student, and pathways to permanent residency, which are linked to the performance of work, following graduation. As a consequence, international students may be incentivised to breach their visa conditions and accept low skilled and poorly paid work after graduation. These incentivised choices contribute to poor employment outcomes for international student graduates, which risks undermining the international education industry. This article explores the nexus between work and education for international students studying in Australia, and the consequences of contradictory approaches to work in the student and residency visa schemes. It contends that addressing these factors would go some way to enabling international student graduates to secure work commensurate with their education and skill level, which would benefit international students, the higher education sector and the economy at large.

Evidence that gender-based pay inequity is higher when pay is secret has led governments to prohibit pay secrecy clauses and give employees the right to discuss and disclose their pay. However, the effectiveness of regulations prohibiting pay secrecy may be constrained by social and organisational norms that preclude discussion of pay, including employee fears of the implications of pay transparency. This article provides insights from interviews with 32 employees and managers from a large Australian financial services company, revealing that perceptions of pay transparency are shaped by organisational rules, social norms, trust in the employing organisation, and fear of the repercussions of knowing pay is unequal. The implications for the effectiveness of the pay transparency measures in the Fair Work Legislation Amendment (Secure Jobs, Better Pay) Act 2022 (Cth) are discussed.

This article examines the challenges of border-crossing science at geopolitical hot spots through the case study of the East Sea (also known as the Sea of Japan). The East Sea is a marginal sea on the north-west Pacific Ocean surrounded by four historically conflicted nations—South Korea, North Korea, Russia, and Japan. Despite vast scientific interest, severe military conflicts have restricted transnational cooperation in this region throughout the late twentieth century. Utilizing personal archives, cruise reports, and interviews with participating scientists, this article examines how an international team of East Asian oceanographers developed material, political, and rhetorical tactics to circumvent and even appropriate complex border problems at the end of the Cold War. The case study suggests that the global history of oceanography should pay further attention to the practical challenges of accessing geopolitically conflicted basins as well as creative strategies that scientists devise to bridge over those troubled waters.

W. E. B. Du Bois theorized that the way Black Americans understand the racial world and their place within it shapes their connections to national identity differently from those of White Americans. This article juxtaposes Du Bois’s theory of racialized subjectivity with Identity Theory’s constructs of prominence and change to examine differences in attachment to American nationhood during a turbulent period of American politics: the Trumpism era. Using data from three waves of the American National Election Studies (2012, 2016, 2020), this study examines the extent to which White and Black Americans viewed their national identities as important before, during, and after Trump’s first presidential administration. I employ “racial identity prominence” as a nuanced measure of race to illustrate a phenomenological element of American national identity that differentially shapes attachment. The findings reveal that the Trumpism period catalyzed significant identity change between 2012 and 2020. Moreover, the degree to which White and Black Americans connected to their national identity across the three election years largely depended on the subjective importance they assigned to their racial identity—that is, their racial identity prominence. The White American archetype was reinforced, as Whites with strong attachment to their racial identity also expressed strong national identity. Interestingly, Black Americans also expressed strong ties to their national identity during this period, particularly those with a strong racial identity. Still, the question of how White and Black Americans envision the country and their place in it remains complex.

This paper reviews a purposive sample of doctoral dissertations in second-language education, completed between 2019 and 2023 at universities in Germany. Among the 79 relevant dissertations found from this period, 18 thematic strands were identified, of which 7 were chosen as being particularly relevant for a more in-depth review: (1) evaluation of specific teaching approaches, (2) (partial) language skills, (3) individual variables, (4) special learner groups, (5) multilingualism pedagogies, (6) digital media, and (7) literature and film pedagogy. We identify relevant topics and relate these to trends in research methodology (qualitative/quantitative/mixed methods). We also discuss the depth and breadth of these dissertations and situate their scholarly contributions within German and international research on additional language education. A comparison with the three previous review articles reveals methodological developments and thematic shifts, highlighting both progress and persistent challenges in German-language doctoral research across nearly two decades of scholarship.

We prove that if $p \geq n^{-(q-6)/2}$, then asymptotically almost surely the binomial random q-uniform hypergraph $\mathcal{G}^{(q)}(n,p)$ contains an (n, q, 2)-Steiner system, provided n satisfies the necessary divisibility conditions.

Women receive a disproportionate share of the online abuse and violent threats made against politicians. Yet, mounting cross-national evidence also suggests that the long-observed gender disparity in citizens’ voting preferences has rapidly diminished – and arguably reversed – in recent decades. Emerging experimental research likewise suggests the broader public in many democratic countries is particularly sensitive to online abuse and threats against women politicians. Herein, we highlight the sexist beliefs of audiences as an important explanation for this apparent inconsistency. Analyzing data from a vignette experiment embedded within a wider survey administered to a demographically representative sample of the British electorate, we demonstrate that the sex of the candidate has only limited influence on observers’ tolerance for threats against politicians. However, respondents that held more sexist attitudes were both more tolerant of violent threats against politicians and particularly tolerant of abuse directed against female candidates. More concerningly, we find that priming sexist respondents to think about female candidates increased support for abusive behaviors against politicians more generally, irrespective of their sex. Our results add to the growing evidence that tolerance for political violence is driven not so much by partisan hostility and ideological polarization as by specific personality traits.

In prior studies, contextual diversity (CD) has been shown to significantly impact word learning, yet gaps remain in understanding its theoretical underpinnings and moderating factors. This research aimed to synthesize trends in CD studies, evaluate the heterogeneity in its definitions and operationalizations, explore its correlation with word learning, and examine potential moderators influencing this relationship. After a literature search and application of screening criteria, we conducted a systematic review and meta-analysis of 20 empirical studies. The primary target population comprises both L1 monolingual and L2 bilingual speakers. Behavioral studies revealed a significant effect of CD on word learning (Cohen’s d = 0.44, p < .001). Eye-tracking data demonstrated significant effects during early and later stages of processing, reflecting heightened attention: first fixation duration: d = −0.365, p = .023, gaze duration: d = −0.574, p = .005, go-past time: d = −0.749, p = .023, and total time: d = −0.691, p = .009. Moderator analysis identified age as a key factor, while gaps in theoretical frameworks and assessments of cognitive moderators were noted. These findings highlight the need for integrating offline and online methods and developing clearer theoretical models to advance our understanding of CD.

Citrus greening is a bacterial disease with no cure or treatment. Since its onset in Florida, orange production statewide has decreased by more than 90%. A recently approved technology consists of injecting antibiotics into tree trunks, which growers expect to improve tree health and increase yield. We use a spatial equilibrium model to conduct an ex-ante analysis of the not-from-concentrate orange juice market to examine the market and welfare impacts of Florida growers’ adoption of antibiotic trunk injections. Results show yield must increase by at least 83% to generate a positive producer surplus when using a discount rate of 10%.

Over the last decade, the Australian Dark Energy (OzDES) collaboration has used Reverberation Mapping to measure the masses of high redshift supermassive black holes. Here we present the final review and analysis of this OzDES reverberation mapping campaign. These observations use $6-7$ years of photometric and spectroscopic observations of 735 Active Galactic Nuclei (AGN) in the redshift range $z\in [0.13, 3.85]$ and bolometric luminosity range $\log_{10}(L_{\mathrm{bol}})\in [44.3, 47.5] \; \mathrm{erg/s}$. Both photometry and spectra are observed in visible wavelengths, allowing for the physical scale of the AGN broad line region to be estimated from reverberations of the H$\beta$, MgII and CIV emission lines. We successfully use reverberation mapping to constrain the masses of 62 super-massive black holes, and combine with existing data to fit a power law to the lag-luminosity relation for the H$\beta$ and MgII lines with a scatter of $\sim0.25$ dex, the tightest yet identified, fit specifically for consistency with high redshift AGN. We fit a similarly constrained relation for CIV, resolving a tension with the low luminosity literature AGN by accounting for selection effects arising from finite survey length. We also examine the impact of emission line width and luminosity (related to accretion rate) in reducing the scatter of these scaling relationships and find no significant improvement over the lag-only approach for any of the three lines. Using these relations, we further estimate the masses and accretion rates of 246 AGN with single epoch methods. We also use these relations to estimate the relative sizes of the H$\beta$, MgII and CIV emitting regions, and find evidence that the MgII emission may occur further out than H$\beta$. In short, we provide a comprehensive benchmark of high redshift AGN reverberation mapping at the close of this most recent generation of surveys, including light curves, time-delays, and a set of significantly improved radius-luminosity relations for use with high-redshift populations.

Archaeological fieldwork in China commonly relies on short-term labor recruited from nearby villages, forming a long-standing mode of collaboration between state-employed staff and local workers. Drawing on sustained field engagement and interviews at the Chengcun City Site of the Han Dynasty, this research examines how locally recruited workers enter, sustain, and experience participation in archaeological practice. Community members often begin archaeological work during agricultural off-seasons and may accumulate decades of experience. Their trajectories vary: some obtain institutional posts, others return to farming, and many continue in project-based employment. These trajectories indicate that funding structures shape employment continuity and welfare access, while skills developed through long-term practice do not always translate into formal professional status. Archaeological labor constitutes a key mechanism in producing excavation knowledge, shaping professional roles, and structuring heritage governance in everyday practice. Viewed through labor trajectories, archaeological professionalization appears uneven, shaped by institutional arrangements, rural livelihood strategies, and localized opportunities. Based on the Chengcun case, this research points to broader dynamics: large-scale projects rely on localized labor regimes while maintaining differentiated forms of recognition and authority. Reconsidering archaeology through labor offers a perspective on knowledge production, participation, and governance.

Timely soybean planting is important for maximizing yield, with farmers tending to plant their crops earlier. However, when a soybean crop is planted ultra-early (before April 15th in Ohio), seedlings are exposed to cold and moist conditions that can lead to a smaller plant population, delayed canopy closure, and reduced ability to compete with weeds. The objective of this study was to evaluate herbicide treatments for their effect on weed development and soybean yield when the crop was planted ultra-early (before April 15) and at a normal time (early to mid-May in Ohio). Weed biomass was significantly reduced when the crop was treated at early postemergence. However, preemergence followed by early postemergence herbicide applications were generally less effective at suppressing weeds than treatments that included an early postemergence and late postemergence application, for which weed density was reduced and weed control was improved later in the season. In 2024, when the number of soybean plants was very low due to freeze damage, an early postemergence application of dicamba + glyphosate and a late postemergence application of glyphosate + glufosinate + S-metolachlor resulted in the greatest weed control and yield from the crop that was planted ultra-early. The results from this study indicate that when soybean was planted ultra-early, treatments that included two postemergence applications, particularly those that included a residual herbicide applied at late postemergence, were better suited to maintain weed suppression later in the season and protect soybean yield potential when the soybean plant population was very low and pressure from grass weeds was high.

As sustainability challenges intensify globally, evaluating the environmental impacts of the Belt and Road Initiative (BRI) has become increasingly important. Using panel data from 176 countries spanning 2003–2022, this study examines the influence of BRI on environmental sustainability using ecological footprint per capita (lnEF) as a comprehensive indicator and difference-in-differences (DiD) methodology. BRI participation leads to a 5 per cent increase in the lnEF among partner countries. Dual-channel analysis shows that renewable energy consumption mitigates ecological pressure, whereas information and communication technology development partially mediates the effects of BRI participation and environmental outcomes. Pronounced heterogeneity effects were observed for (i) countries joining between 2016 and 2019 (in Europe, Central Asia, the Middle East and North Africa), and (ii) countries in upper-middle- and high-income groups. Propensity score matching–DiD and robustness checks showed consistent findings. This study offers policy recommendations that emphasize environmental assessments, green technology support and international cooperation on sustainability.

The primordial helium mass fraction, $Y_{p}$, is a key observational pillar of Big Bang nucleosynthesis and a sensitive probe of early-Universe physics. Over the past several decades, numerous observational $Y_{p}$ determinations have been published using a wide range of astrophysical tracers and cosmological techniques. Although recent measurements exhibit striking convergence and increasingly small uncertainties, the statistical and historical context of this consensus has not been examined systematically. Here, we compile and analyse a comprehensive dataset of observational $Y_{p}$ determinations published between the late-1960s and 2022. The final sample comprises 143 reported values spanning multiple tracers. We find clear evidence for long-term convergence in published $Y_{p}$ values, punctuated by statistically significant change points in the mid-2000s and early 2010s. Careful examination reveals that many extragalactic Hii-region determinations are not fully independent, relying on re-analyses or partial reuse of a limited number of observational datasets. This reduces the effective number of independent constraints and provides important context for interpreting the precision of recent results. Our findings do not challenge the overall consistency of modern $Y_{p}$ determinations with standard cosmology, but they underscore the importance of accounting for data dependence, methodological homogeneity and historical evolution when synthesising measurements.

This article surveys nonlinear model reduction methods that remain effective in regimes where linear reduced-space approximations are intrinsically inefficient, such as transport-dominated problems with wave-like phenomena and moving coherent structures, which are commonly associated with the Kolmogorov barrier. The article organizes nonlinear model reduction techniques around three key elements – nonlinear parametrizations, reduced dynamics and online solvers – and categorizes existing approaches into transformation-based methods, online adaptive techniques, and formulations that combine generic nonlinear parametrizations with instantaneous residual minimization.

Digital Twin Construction (DTC) is a data-centric mode of construction that leverages digital twin technologies to maintain a continuously updated representation of a project and to enable short cycle Plan Do Check Act (PDCA) planning and control with continuous feedback and improvement. Industrial implementations reported to date have been too narrow in scope and too few in number to provide comprehensive proof of feasibility and empirical evidence of impacts. We address these gaps using a laboratory setup that implements a complete DTC PDCA workflow for a precast residential project. The experimental DTC system stores project intent, monitors and captures current status, and supports human in the loop replanning or automated optimization across factory production, logistics, and erection on site for a 1:25 scale model building. Validation through numerous full construction project runs demonstrates consistent end-to-end operation and practical usability. The testbed itself provides a reference architecture for DTC systems and a platform for controlled and replicable experiments that provide comparable quantitative evidence on DTC impacts under varied levels of automation.