Priority Information Research Articles

Spatial and temporal variability in summertime dissolved carbon dioxide and methane in temperate ponds and shallow lakes

AbstractSmall waterbodies have potentially high greenhouse gas emissions relative to their small footprint on the landscape, although there is high uncertainty in model estimates. Scaling their carbon dioxide (CO2) and methane (CH4) exchange with the atmosphere remains challenging due to an incomplete understanding and characterization of spatial and temporal variability in CO2 and CH4. Here, we measured partial pressures of CO2 (pCO2) and CH4 (pCH4) across 30 ponds and shallow lakes during summer in temperate regions of Europe and North America. We sampled each waterbody in three locations at three times during the growing season, and tested which physical, chemical, and biological characteristics related to the means and variability of pCO2 and pCH4 in space and time. Summer means of pCO2 and pCH4 were inversely related to waterbody size and positively related to floating vegetative cover; pCO2 was also positively related to dissolved phosphorus. Temporal variability in partial pressure in both gases weas greater than spatial variability. Although sampling on a single date was likely to misestimate mean seasonal pCO2 by up to 26%, mean seasonal pCH4 could be misestimated by up to 64.5%. Shallower systems displayed the most temporal variability in pCH4 and waterbodies with more vegetation cover had lower temporal variability. Inland waters remain one of the most uncertain components of the global carbon budget; understanding spatial and temporal variability will ultimately help us to constrain our estimates and inform research priorities.

Animal population decline and recovery after severe fire: Relating ecological and life history traits with expert estimates of population impacts from the Australian 2019-20 megafires

Catastrophic megafires can increase extinction risks; identifying species priorities for management and policy support is critical for preparing and responding to future fires. However, empirical data on population loss and recovery post-fire, especially megafire, are limited and taxonomically biased. These gaps could be bridged if species' morphological, behavioural, ecological and life history traits indicated their fire responses. Using expert elicitation that estimated population changes following the 2019–20 Australian megafires for 142 terrestrial and aquatic animal species (from every vertebrate class, one invertebrate group), we examined whether expert estimates of fire-related mortality, mortality in the year post-fire, and recovery trajectories over 10 years/three generations post-fire, were related to species traits. Expert estimates for fire-related mortality were lower for species that could potentially flee or shelter from fire, and that associated with fire-prone habitats. Post-fire mortality estimates were linked to diet, diet specialisation, home range size, and susceptibility to introduced herbivores that damage or compete for resources. Longer-term population recovery estimates were linked to diet/habitat specialisation, susceptibility to introduced species; species with slower life histories and shorter subadult dispersal distances also had lower recovery estimates. Across animal groups, experts estimated that recovery was poorest for species with pre-fire population decline and more threatened conservation status. Sustained management is likely needed to recover species with habitat and diet specialisations, slower life histories, pre-existing declines and threatened conservation statuses. This study shows that traits could help inform management priorities before and after future megafires, but further empirical data on animal fire response is essential.

Image-text coherence and its implications for multimodal AI.

Human communication often combines imagery and text into integrated presentations, especially online. In this paper, we show how image-text coherence relations can be used to model the pragmatics of image-text presentations in AI systems. In contrast to alternative frameworks that characterize image-text presentations in terms of the priority, relevance, or overlap of information across modalities, coherence theory postulates that each unit of a discourse stands in specific pragmatic relations to other parts of the discourse, with each relation involving its own information goals and inferential connections. Text accompanying an image may, for example, characterize what's visible in the image, explain how the image was obtained, offer the author's appraisal of or reaction to the depicted situation, and so forth. The advantage of coherence theory is that it provides a simple, robust, and effective abstraction of communicative goals for practical applications. To argue this, we review case studies describing coherence in image-text data sets, predicting coherence from few-shot annotations, and coherence models of image-text tasks such as caption generation and caption evaluation.

Emission forecasting from open burning of crop straw and policy analysis: The case for China

The open burning of crop straw releases greenhouse and harmful gases, and pollutants, which hinder the reduction of carbon emissions and attainment of environmental protection commitments in China. In this study, based on the fractional discrete grey model (FDGM (1,1)) and the new information priority discrete grey model (NIPDGM (1,1)), an alternative weighted hybrid discrete grey model (WHDGM (1,1)) coupled with a particle swarm optimization algorithm was developed to forecast the total crop straw production, quantity of crop straw open burning, and burning emissions in China. The results have shown that the proposed WHDGM (1,1) had the highest simulation accuracy compared to NIPDGM (1,1) and FDGM (1,1). Based on the WHDGM (1,1), predictions for annual crop straw production, crop straw open burning, and induced CO, CO2, NOx, and PM2.5 emissions are conducted, respectively. By 2025, crop straw production and crop straw open burning will increase by 10.5% and 7.2%, respectively. Relevant CO, CO2, NOx, and PM2.5 will be augmented by 7.4%, 7.7%, 5.6%, and 9.6%, respectively. Countermeasures for controlling crop straw open burning and relevant policy suggestions have been discussed. This study offers practical insights and guidance for the strategic control of crop straw open burning, therefore, ensuring the achievement of carbon neutrality and supporting environmental commitment.

Acoustic emission precursor information of rock failure under true triaxial loading and unloading conditions

Rock failure generally leads to serious consequences, and it is significant to obtain the precursor information prior to failure using associated techniques. Acoustic emission (AE) is one of the indispensable methods for disaster warning of hard and brittle rock. Acoustic emission detection technology can effectively monitor real-time information about changes in the rock interior and predict the process of rock damage failure. To probe the relationship among the AE precursor information of red sandstone under different intermediate principal stresses, an experimental study was conducted by us to examine the alterations in AE parameters during the failure of red sandstone under both loading and unloading circumstances. The study shows that the ringing count rate and absolute energy versus time curves are divided into four stages, namely, quiet, frequent, sudden increase and decline periods. The cumulative count curve is also divided into four phases: pre-unloading period, post-unloading period, sharp increase period, and decrease period. With the rise of the intermediate principal stress, the ringing count rate and energy exhibited during the frequent period of AE demonstrate a consistent increase, with a larger increase in the maximum value and a smaller increase in the average value. In addition, the peak value of AE signals during failure also increases accordingly. The occurrence moment and clarity of the frequent period determine the reliability and priority of the information related to the rock’s failure precursor; moreover, the reliability and priority of the AE precursor information will increase with the increase of the intermediate principal stress. After comparison, it is found that the AE precursor information occurs prior to the thermal infrared precursor information.

Incidence of selected cancers in Non-Hispanic American Indian and Alaska Native adolescent and young adult populations, 1999–2019

Studies have highlighted geographic variation in cancer incidence rates among American Indian and Alaska Native (AI/AN) populations. This is the first study to comprehensively evaluate incidence rates and trends among non-Hispanic AI/AN (NH-AI/AN) adolescents and young adults (AYAs) ages 15-39 years. Using the United States Cancer Statistics AI/AN Incidence Analytic Database, we identified all malignant cancer cases for NH-AI/AN AYA populations for the years 1999-2019. We calculated age-adjusted incidence rates (per 100,000) for NH-AI/AN populations overall, by region, and by age group. We calculated the total percent change in the incidence of leading AYA cancers between 1999 and 2019, and trends by region and cancer type using Joinpoint analysis. Testicular (13.6) and breast (19.0) cancers had the highest incidence of all AYA cancers in NH-AI/AN males and females, respectively. Overall AYA cancer rates increased by 1.4% in NH-AI/AN males and 1.8% in NH-AI/AN females annually between 1999 and 2019. Increases were observed by age group and geographic region. This study describes regional differences in incidence rates of AYA cancers among NH-AI/AN populations. This data can help inform resource and cancer control priorities and strategies to reduce cancer risk and enhance access to quality diagnostic and treatment services for this population.

Building Resilient Communities: The Environmental Observatory for Mining Projects and Climate Change Indicators

Public environmental information can improve industry performance, reduce environmental conflicts, and foster informed citizenship. The latter is directly linked to resilience because it is a “process that enables people to learn together, support experimentation, and increase the potential for (social and technological) innovation”. Importantly, the transparency and disclosure of environmental information alone do not have the desired impact; the general public may have access to information but not understand the content. It is necessary to reframe the technical language of information to reach broader stakeholder understanding. The Environmental Observatory for Mining Projects is an applied research project that aims to provide a public information access system for diverse stakeholders. It integrates data from various public services and makes them available to a variety of stakeholders, including the general public, through a web server and application that facilitate accessibility and understanding by using the co-creation methodology for public services. As a result of the project, the authors identified 25 indicators, six of which relate to climate change, including greenhouse gas emissions, water pollution, air pollution, hazardous waste, and tailing deposit locations. These indicators are relevant for decision making through the combined knowledge of public policies, information priorities on the impacts and vulnerabilities of climate change, and more practical issues related to data availability. The authors conclude that environmental information systems must provide people with essential data, but that such information must also be understandable, manageable, comparable, and interoperable so as to promote access to crucial information for resilient communities.

Machine-Learning-Enhanced Blockchain Consensus With Transaction Prioritization for Smart Cities

In the given technology-driven era, smart cities are the next frontier of technology, and these smart cities aim to improve the quality of people’s lives. In this article, we introduce such future Internet of Things (IoT)-based smart cities that leverage blockchain technology. Particularly, when there are multiple parties involved, blockchain helps in improving the security and transparency of the system in an efficient manner. However, if a current fee-based or first-come–first-serve-based processing is used, emergency events may get delayed and even threaten people’s lives. Thus, there is a need for transaction prioritization based on the priority of information and a dynamic block creation mechanism for efficient data recording and faster event response. Also, our system focuses on the consortium blockchain maintained by a group of members working across different organizations to provide more efficiency. The leader election procedure in such a consortium blockchain becomes more important for the transaction prioritization process to take place honestly. Hence, in our proposed consensus protocol, we deploy a machine-learning (ML) algorithm to achieve efficient leader election, based on which a novel dynamic block creation algorithm is designed. Also, to ensure the honest block generation behavior of the leader, a peer-prediction-based verification mechanism is proposed. Both security analysis and simulation experiments are carried out to demonstrate the robustness, accuracy, and efficiency of our proposed scheme.

Public Information Priorities across Weather Hazards and Time Scales

Abstract As the abundance of weather forecast guidance continues to grow, communicators will have to prioritize what types of information to pass on to decision-makers. This work aims to evaluate how members of the public prioritize weather forecast attributes (including information about location, timing, chance, severity, impacts, and protective actions) on average and across event timelines in the severe, tropical, and winter weather domains. Data from three demographically representative surveys of U.S. adults indicate that members of the public generally prioritize information about event location, timing, and severity when evaluating the importance of forecast attributes. This pattern is largely consistent across hazard domains but varies across event timelines. In early stages of a forecast (such as the outlook time scale), people generally prioritize information about chance and location. In middle stages (watch time scale), event timing and severity become more important. In late stages (warning time scale), information about protective actions is a higher priority, especially for people with less exposure to a hazard.

A spatial lagged multivariate discrete grey model for forecasting an economy-energy-environment system

To perform better future trend prediction for an economy-energy-environment (3E) system and address the shortcomings of traditional multivariate grey models, this paper introduces a spatial correlation term into the multivariate discrete grey model, thus creating the SLDGM(1,n) model, and improves the final calculation of the model according to the priority of new information. The validity of the SLDGM(1,n) model is assessed using data from the 3E system in North China, and the SLDGM(1,n) model is applied to predict the future trends of the 3E system in North China. The following conclusions are obtained. First, the introduction of the spatial correlation term and the improvement of the final calculation method are reasonable; the prediction accuracy of the multivariate grey model is improved, and multiple systems are modeled simultaneously. Second, the SLDGM(1,n) model calculates the spatial spillover effect, and according to the simulation results for North China from 2010 to 2019, Hebei's energy consumption and carbon emissions are subject to the largest influence from other provinces, while its economic development level is subject to the smallest influence, and the carbon emissions of Shanxi and Inner Mongolia are subject to a negative spatial influence effect. Third, the prediction results indicate that under the effect of spatial correlation, the energy consumption of all five provinces in North China will continue to rise; the carbon emissions of Beijing will gradually decline while the carbon emissions of the other four provinces will all gradually rise, and the per capita GDP of the five provinces is expected to increase by more than 50% by 2025.

The recursive grey model and its application

The fixed structure parameters limit the performance of grey prediction algorithm in unsmoothed time series prediction tasks. Based on the mechanism of recursive iteration, this study proposes a recursive grey model to predict the future trend of renewable energy generation in China. The proposed method has the following improvements: the first is the priority of new information. By introducing a memory factor parameter into the objective function, recursive grey model gives more influence to new observations. The second is dynamic updating scheme of structure parameters and improved iteration base values. The proposed model uses recursive method to solve the structure parameters of each observation, and the new parameters can inherit the previous experience. The third is stable forecasting performance. Based on the principle of minimizing the prediction error of in-sample data, the memory factor optimization method is given. Without additional verification set, recursive grey model can synchronize training and test of in-sample data to avoid over fitting. Finally, the proposed model is applied to predict China's renewable energy generation. The forecast results show that in the next few years, China's hydropower, wind power and solar power generation will grow at an average annual growth rate of 2.6%, 20.7% and 24.9%, respectively. It can be predicted that China's hydropower generation, wind power generation and solar power generation will reach 1475 billion kWh, 3094 billion kWh and 1352 billion kWh, respectively in 2030.

Infant food users' perceptions of safety: A web-based analysis approach.

This paper aims to explore consumer beliefs about health hazards in infant foods by analyzing data gathered from the web, focusing on forums for parents in the UK. After selecting a subset of posts and classifying them by topic, according to the food product discussed and the health hazard discussed, two types of analyses were performed. Pearson correlation of term-occurrences highlighted what hazard-product pairs are most prevalent. Ordinary Least Squares (OLS) regression performed on sentiment measures generated from the texts provided significant results indicating positive or negative sentiment, objective or subjective language, and confident or unconfident modality associated with different food products and health hazards. The results allow comparison between perceptions obtained in different countries in Europe and may lead to recommendations concerning information and communication priorities.

Forecasting Chinese Electricity Consumption Based on Grey Seasonal Model with New Information Priority

The total electricity consumption in China includes almost all the electricity consumption from all fields, which can reflect the overall situation of China’s electricity consumption, and it is of great significance to forecast it. This paper develops a novel grey Holt-Winters model based on the new information priority cycle accumulation operator, known as the NCGHW model for short, in order to effectively forecast the total electricity consumption in China. First of all, this paper proposes the new information priority cycle accumulation operator to mine the internal law of data while maintaining periodicity in the accumulated data. Then, based on the one-order accumulation sequence generated by the new operator, the framework of the Holt-Winters model is used to build a new model. Finally, according to the characteristics of the data itself, the LBFGS algorithm is used to find the most suitable parameters for the model. In order to model and analyze the fine-grained measurement of the total electricity consumption in China, we study the monthly and quarterly data, respectively. The new model and the contrast models are applied to the two sequences for simulation and prediction. The performance of the model is discussed through relevant evaluation criteria. The results show that the new model has sufficient capacity to forecast the monthly and quarterly total electricity consumption. It is the best choice for the total electricity consumption in China.

Neural unscrambling of temporal information during a nonlinear narrative.

Although we must experience our lives chronologically, storytellers often manipulate the order in which they relay events. How the brain processes temporal information while encoding a nonlinear narrative remains unclear. Here, we use functional magnetic resonance imaging during movie watching to investigate which brain regions are sensitive to information about time in a narrative and test whether the representation of temporal context across a narrative is more influenced by the order in which events are presented or their underlying chronological sequence. Results indicate that medial parietal regions are sensitive to cued jumps through time over and above other changes in context (i.e., location). Moreover, when processing non-chronological narrative information, the precuneus and posterior cingulate engage in on-the-fly temporal unscrambling to represent information chronologically. Specifically, days that are closer together in chronological time are represented more similarly regardless of when they are presented in the movie, and this representation is consistent across participants. Additional analyses reveal a strong spatial signature associated with higher magnitude jumps through time. These findings are consistent with prior theorizing on medial parietal regions as central to maintaining and updating narrative situation models, and suggest the priority of chronological information when encoding narrative events.

A global perspective of advanced practice nursing research: A review of systematic reviews protocol.

In 2020, the World Health Organization called for the expansion and greater recognition of all nursing roles, including advanced practice nurses (APNs), to better meet patient care needs. As defined by the International Council of Nurses (ICN), the two most common APN roles include nurse practitioners (NPs) and clinical nurse specialists (CNSs). They help ensure care to communities as well as patients and families with acute, chronic or complex conditions. Moreover, APNs support providers to deliver high quality care and improve access to services. Currently, there is much variability in the use of advanced practice nursing roles globally. A clearer understanding of the roles that are in place across the globe, and how they are being used will support greater role harmonization, and inform global priorities for advanced practice nursing education, research, and policy reform. To identify current gaps in advanced practice nursing research globally. This review of systematic reviews will provide a description of the current state of the research, including gaps, on advanced practice nursing globally. We will include reviews that examine APNs, NPs or CNSs using recognized role definitions. We will search the CINAHL, EMBASE, Global Health, HealthStar, PubMed, Medline, Cochrane Library Database of Systematic Reviews and Controlled Trials Register, Database of Abstracts of Reviews of Effects, Joanna Briggs Institute, and Web of Science electronic databases for reviews published from January 2011 onwards, with no restrictions on jurisdiction or language. We will search the grey literature and hand search the reference lists of all relevant reviews to identify additional studies. We will extract country, patient, provider, health system, educational, and policy/scope of practice data. We will assess the quality of each included review using the CASP criteria, and summarize their findings. This review of systematic reviews protocol was developed following the PRISMA-P recommendations. CRD42021278532.

Sustainability oriented innovation and organizational values: a cluster analysis

Purpose: Sustainability is an important priority for CEOs according to a recent Mckinsey (2021) survey. However, despite growing pressure from capital investors, employees and consumers, few organizations are satisfied with the sustainability objectives achieved beyond objectives related to economic savings. The sustainability challenge is even more difficult for organizations when dealing with designing their innovation portfolio strategies since the markets´ demands and competitors´ strategies may contradict organizations’ sustainability objectives and thus jeopardize their continuity. Some researchers argue that a commitment to sustainability in organizations is not so much a matter of managerial practice but rather is rooted in organizational values (Globocnik et al., 2020). Therefore, this research aims to explore what types of organizational values more effectively promote sustainability-oriented innovation in organizations. Using as a conceptual framework the competing values theory (Quinn & Rohrbaugh, 1983), and adding one dimension, risk aversion, we empirically define some clusters of business typologies from which we derive patterns of value profiles. We show how these clusters’ patterns of values relate to the success of a firm’s sustainability-oriented innovation.Methodology: To make sense of our literature review and ensure managerial relevance, we surveyed 128 senior managers from different industries and countries to understand how their perceived organizational values may impact their firms’ sustainability-oriented innovation success. As a result, we group the studied organizations into four clusters according to the informed organizational values, and we assess how the different clusters are more or less prone to succeed with a sustainability-oriented innovation strategy.Findings: Our results show that not all organizational values contribute equally to the success of sustainability-oriented innovation in the market. As a theoretical contribution, we advance current knowledge about how organizational values may impact sustainability-oriented innovation success by providing a framework to measure and follow up on the evolution of necessary organizational values to embrace sustainability-oriented innovation within an organization. From a managerial perspective, we advance knowledge on how organizational values should evolve and change to efficiently deliver more sustainability-oriented innovation. In addition, we describe specific values that organizations should measure and track and otherwise establish as an important first step toward implementing sustainability-oriented innovation within them.Originality: Our research provides original results by expanding current knowledge on organizational values to better understand which values more efficiently promote competitive sustainability-oriented innovation in organizations. We expand the four organizational cultural archetypes of organizational values to develop a more flexible and actionable framework of five dimensions by adding an important dimension to the model, risk aversion. Together, these dimensions generate new insights through a cluster analysis of organizational differences and inform priorities and courses of actions to undertake.Research limitations and implications: This research is based on self-report surveys and is therefore exposed to the expected limitations of the survey research methodology.

ІНФОРМАЦІЙНО-АНАЛІТИЧНА ПІДТРИМКА ДІЯЛЬНОСТІ ПОЛІЦІЇ ЯК СКЛАДОВА ЧАСТИНА СИСТЕМИ ЗАХОДІВ ІЗ ЗАБЕЗПЕЧЕННЯ ІНФОРМАЦІЙНОЇ БЕЗПЕКИ ДЕРЖАВИ

The purpose of this article is to determine the essence and content of information and analytical support for police activities as a component of the system of measures to ensure the information security of the state, in particular through the use of appropriate organizational, legal and technical means by the authorized units. It has been established that the information and analytical support of police activities in all areas of authority creates prerequisites for identifying, stopping and eliminating threats to information security, as well as direct administration of such information. It has been confirmed that among the structural units of the National Police, the units of information and analytical support directly administer the use of modern information technologies by ensuring the functioning of the IPNP within the framework of the Ministry of Internal Affairs with the operation of the relevant array of information resources of general and special legal regimes. The substantive elements of the activities of the information and analytical support units of the National Police of Ukraine are characterized, among which a significant place is allocated to the creation and support of the operation of an array of information resources, which are a set of defined groups of interconnected documented units of information that are formed and combined in the automated information systems of the sub- entities of the UES of the Ministry of Internal Affairs on certain grounds, including those specified in the list of priority information resources of the UES of the Ministry of Internal Affairs. The issue of administration of relevant subsystems of the EIS of the Ministry of Internal Affairs is also highlighted as a significant component of information and analytical support for police activities, including special attention paid to the functioning of the Information Portal of the National Police of Ukraine. Among the above components, a decisive place in the context of the subject of research is given to the formation of databases of various nature, which are differentiated by the content of relevant information into: 1) determining (law enforcement) nature; 2) of a related or secondary character for the police within the powers of public authorities; 3) of an administrative and security nature.

Islam in the Russian Media

Islam, the second-largest religion (after Orthodoxy) in terms of clergy in Russia, seems to be quite a popular topic in the modern Russian media. Therefore, the task of understanding the information provided is not only relevant nowadays but inevitably puts some pivotal questions on the agenda: Does this context meet public demand? What approaches do the Russian media take in their coverage of this religion? These questions have made writing this article a priority. Along with the situation with the Muslim population of Russia, the author explores the historical evolution of the Muslim press in Russia over the course of a few centuries. The current media focus on Muslim territories is also considered. On the one hand, Islam has traditionally been among the media’s interests, but on the other hand, the specifics of relations between authorities and the media define the quality of the information provided. This dualistic media approach to Islam was inherited from past information priorities and continues today. In order to envisage the position of the media in this regard, the author carefully investigates the politics of three leading Russian television channels, Channel 1, Rossiya-1, and NTV, all of which regularly cover this subject, particularly in their news programs. Sorting through empirical examples, the author comes to the conclusion that problematic aspects of the topic are not covered by the media. This negatively affects the media content and clashes with journalistic principles. The analysis offers an opportunity to make prognoses about the media’s future position on Islam.

STATE REGULATION OF PUBLISHING: PROSPECTS FOR DEVELOPMENT

The experience of most countries confirms that the development of modern information technologies does not reduce people's interest in books. The demand for publishing products remains stable, and in the context of the dynamic development of the digital economy and the priority of information as a resource for sustainable development, it is even growing. Thus, in the EU countries, 6 to 8 books are published per capita per year. In Ukraine, there are significantly different trends, because in 2020 the annual circulation of books in Ukraine amounted to 20.2 million copies, that is, 0.48 copies of books and brochures per one inhabitant of Ukraine. Under such conditions, the development of publishing entities requires strategic and conceptual organizational and financial support from the state in the context of more efficient use of limited financial resources. Since 2005, Ukraine has been implementing the "Ukrainian Book" program, which along with providing tax benefits to publishers and book distributors is a form of state support for publishing. The results of the audit of the effectiveness of the use of funds proved that the effectiveness of the use of state budget funds is not high enough, in particular due to the imperfection of the criteria for selecting publications. Based on the results of the study, a list of such criteria was formed. The methodological principles of expert evaluation of book publications declared by the subject of publishing business in accordance with the established criteria for the selection of book products using points have been formed. An evaluation scale based on the selection criteria was developed. Additional characteristics that specify the main criteria for selecting publications included in the program and financed from the budget are proposed. The number of the expert group (7-15 persons) is substantiated, which ensures the reliability of the examination. The developed methodological and practical principles are intended to partially solve the existing problems by establishing scientifically based criteria for more efficient use of state budget funds and satisfying the reading interest of Ukrainian citizens.

Reconceptualizing Stigmas in Aged Care: A Typology of Stigmatizing Discourses in the Aged-Care Context.

Stigmatizing discourses surrounding aged care is complex. The stigma associated with people working in aged care is often conflated with negative evaluations about older adults who receive care and/or the institutions and systems that provide these services. This lack of nuance hampers productive dialogue in gerontology required for making sense of the stigmas attached to entities and systems. We propose that an interdisciplinary approach drawing on gerontology, psychology, and linguistics would facilitate a greater understanding of the stigma of aged care. Specifically, a discourse approach underpinned by Stigma Theory and Systemic Functional Linguistics can clarify the different stigmatizing discourses associated with aged-care entities and systems, and inform priorities for interventions targeting each discourse category identified. APPRAISAL, a linguistics framework, was employed to analyze evaluative language in 660 submissions published in the Australian Royal Commission into Aged Care. Through applying predefined language-based criteria, we distinguished between multiple stigmatizing discourses that were interrelated but conceptually distinct in terms of attitude types and targets. Twelve categories of stigmatizing discourses derived from the linguistic analysis established a typology. This typology conceptualized different ways stigma can be meaningfully understood in the aged-care context. By employing this typology, 12 intervention priorities were also identified. This interdisciplinary approach enabled us to examine the diversity and complexity of the social construction of stigma in the public domain. We argue that understanding these linguistic patterns can assist with designing targeted aged-care interventions and policies.