dataesr/scientific-paragraphs-categorization huggingface dataset:
It is also notable that about half of private spending on PHC (most of which is out of pocket in LMICs) is for medical goods purchased outside health services (figure  2 ). Much of this is likely to be for medicines; for example, The Lancet Commission on Essential Medicines for Universal Health Coverage 49 reported that more than 62% of pharmaceutical expenditure in LMICs was from private sources, which is likely to be mostly out-ofpocket spending considering the low levels of prepaid and pooled resources. In LMICs, the largest share of government expenditure is for outpatient care. Within this spending category, government health spending is highly skewed towards health-worker salaries. WHO's analysis of the Global Health Expenditure Database indicates that for 136 countries, 57% of public spending on health is allocated to wages.
Limitations of our analyses There are limitations to these analyses. First, use of the WHO's broad PHC expenditure definition has the effect of biasing the estimates of PHC spending upwards (because of the inclusion of outpatient services provided in hospitals). Any definition that uses a narrower scope would produce lower estimates of PHC expenditure. For example, in 2019, the OECD reported that spending on primary care within ambulatory settings represented just 12% of health expenditure; this increases to 17% when PHC services delivered in hospital settings are included, and to 34% by including retail pharmaceuticals. 48 econd, data are only available for 95 out of 192 countries and for a single point in time. The spending estimates for some income groups are affected by the small number of countries in each group.
Most importantly for our purposes, the absence of consistent and comparable data over time means that it is not possible to easily identify which countries are increasing or sustaining their commitments to PHC. Therefore, although these results are informative, throughout the report we also include more qualitative assessments of countries' progression towards adequate financing for PHC. Even with our limited dataset, we argue that LMICs need to spend more on PHC to provide equitable and universal access PHC that is people centred. Further, the Commission contends that adopting a definition of PHC that is consistent with the vision of providing health care at the lowest possible level, and then supporting countries to collect and report data disaggregated in this way, are essential steps toward improving the quality of national data on PHC expenditure.
Organisation and provider payment for PHC Countries differ widely in terms of how PHC is structured and organised, including whether PHC includes community health workers and how they link to health facilities. Yet, although the availability of data on PHC expenditure in LMICs is improving, there is still little systematically collected cross-country data on the financial arrangements of LMIC health systems and provider payment structures. This contrasts with the data  The Lancet Global Health Commissions collected from OECD countries, for which the Health System Characteristics Survey provides comparable data on how countries finance, deliver, allocate resources to, and govern their health systems. 42 To address this important data gap, in this Commission, we did our own cross-sectional survey in LMICs with the aim of collecting data on the key financing-related features of how PHC is organised, and on how PHC providers are paid.
Capitation payment, alone or in combination with other payment methods, is used in almost 40% of middle-income countries. Our survey also found that in countries where capitation is used, around two-thirds of PHC systems adjust the payment amounts to reflect variations in health needs (data not shown). These findings from this Commission's survey support other evidence about the role of user payments in low-and lower-middle-income countries, and show that countries at higher levels of income are making greater The Lancet Global Health Commissions use of capitation or blended payment as part of the move towards paying for people-centred PHC. These new data also provide a baseline for future efforts to track developments in PHC financing in LMICs.
Payment of community health workers The Commission's provider payment survey also collected data on how community health workers are paid. Figure  8  shows that more than 80% of lower-middle-income countries and more than 90% of low-income countries reported having some form of community health workers, compared with just over half of upper-middle-income countries. The most common form of payment for community health workers was by salary, although payment per day or per activity was also common in low-income and lower-middle-income countries. A small minority of countries have their community health workers paid in kind only, such as gifts or training; no payment for community health workers was reported only in a small minority (less than 5%) of low-income countries. Evidence on different ways of paying community health workers is presented in section 5.
Rigorous research in this area is urgently needed. Second, digital technologies offer great promise to improve the efficiency of resource mobilisation and purchasing arrangements; however, caution is warranted. There are risks, such as fragmentation if it leads to multiple small funding pools or parallel electronic patient information systems. Another risk is misalignment with UHC equity principles; for example, for the moment, digital access is much higher in cities, although this is changing rapidly. Third, to date, digital technologies related to financing have mostly been applied to health-care purchasing. For example, in the Philippines, digitised claims analysis using artificial intelligence is being used to detect fraud;  57  in India, provider payment has been facilitated through an The Lancet Global Health Commissions online system for data reporting and online pay-forperformance of Accredited Social Health Activists.
The Lancet Global Health Commissions would be helpful to PHC, using other policy levers as necessary. At budget execution stage, a well-developed resource allocation formula can be a useful starting point for improving allocation of financing to PHC. Even a simple per-capita formula, with risk equalisation and performance and quality incentives added as the system develops, can begin to foster equity in universal coverage of a basic package of primary care services. For a formula to be effective, however, other reforms that link budget allocations to PHC are also needed. For any of these policy levers to be feasible, various health system and financial capacities need to be strengthened as well, such as budget management capacity at the Ministry of Health, high-quality data on health status and needs, and effective accounting practices.
156 ven a perfectly-designed capitation-based blended payment system cannot work without basic supporting functions in place (figure  11 ). These will need to develop and evolve as the payment system becomes more sophisticated. It is possible that digital technologies can help to support the evolution of the provider payment system but this remains to be seen (appendix p 35). We describe the main basic supporting functions. • Routine data capture and electronic record systems that are interoperable across datasets, ideally for the whole country, are needed to support complex payment systems. This is an iterative process: requiring data for payment leads to better data, which in turn allows for implementation of a more sophisticated payment system. The capacity to analyse and interpret data should be strengthened if policymakers are to act on data-driven evidence.
Major ongoing reforms to the structure and delivery of health services seek to address some of these challenges. 188 he Lancet Global Health Commissions population enrolment list or database must be accurate because payments to providers under capitation are influenced by the number of individuals enrolled with that provider. The method of creating the list and giving providers access to it should be transparent so providers trust the list and their final payment amounts. Data are also necessary for population characteristics monitoring. To adjust population-based payment rates for need, detailed data on the key characteristics of the registered population are required. Last, data are necessary for service delivery performance monitoring because it is important to capture information on clinical care, health-care use, and patient experience to understand how well PHC providers are addressing population needs and to monitor undesirable behaviours, such as underprovision and excess referral.
The Lancet Global Health Commissions Communities and civil society groups should demand changes. Communities should engage in efforts to hold PHC providers accountable, and be included as partners in monitoring progress. To that end, a key priority for civil society groups should be building the capacity of communities to undertake these functions. Governments should facilitate this accountability by producing data to enable monitoring. Health-care providers and their representative organisations should actively participate in efforts to reform PHC financing arrangements. Providers must engage in the design of payment reforms, understand the implications of proposed changes to provider payment systems, and take any and all opportunities to provide people-centred health care fostered by reformed financing arrangements.
All stakeholders should undertake ongoing efforts to strengthen the health system's basic functions, including data collection and analysis of resource flows and health impacts; monitoring, evaluation, and learning systems; public finance management systems that enable resources to reach frontline providers; and capacity of providers to manage funds effectively. Investment in such basic functions is needed in conjunction with investment in PHC. (4) Global agencies should reform the way PHC expenditure data are collected, classified, and reported A new reporting item (ie, memorandum item) on PHC should be defined and included in countries' annual reporting of health expenditures to WHO for the Global Health Expenditure Database. In the meantime, current reporting should be adapted to be based on a cross-classification of functions and providers (such as the one used by the OECD).
Global Health Expenditure Database reports total PHC spending data but no disaggregation by financial source (ie government, external, and private [Bosnia and Herzegovina, Democratic Republic of Congo, Ethiopia, Ghana, and Uruguay]). Only five high-income countries report external funding for PHC (Barbados, Mauritius, Seychelles, St Kitts and Nevis, and Trinidad and Tobago). For other high-income countries external spending is negligible or zero. Averages are unweighted means across countries. To calculate the average of ratios, we calculated the ratio for each country and took the average for each income group. The sum of government, external, and out-of-pocket spending will not be equal to the total spending due to the omission of other types of private spending, such as voluntary private insurance.
The gap is bigger in high-income countries because private insurance is more common in high-income countries. Although out-of-pocket spending on PHC is available in the OECD database, WHO only reports domestic private spending on PHC. To estimate the out-of-pocket spending for PHC in low-income to middle-income countries, we took the ratio of total out-of-pocket spending on health to total domestic private spending on health and multiplied it by private spending for PHC for each country.
The Lancet Global Health Commissions Emanuel Gloria  ( GECC Development Services, Pasig City, Philippines ). Estonia case study was undertaken by  Kaija Kasekamp , (PhD candidate,  University of Tartu, Tartu, Estonia );  Triin Habicht , ( WHO Barcelona Office for Health System Financing, Barcelona, Spain );  Ruth Kalda  ( University of Tartu, Tartu, Estonia ). Finland case study was undertaken by  Ilmo Keskimäki  ( Research Professor, Finnish Institute for Health and Welfare, Helsinki, Finland ; and Professor of  Health Services Research, Tampere University, Tampere, Finland ). New Zealand case study was undertaken by  Jacqueline Cummings  ( Independent Health Services and Policy Consultant, Wellington, New Zealand ). Shaheda Viriyathorn ,  Anond Kulthanmanusorn ,  Walaiporn Patcharanarumol , and  Viroj Tangcharoensathien  ( International Health Policy Program, Ministry of Public Health, Bangkok, Thailand ) provided additional data for sections 2 and 4.
Level of spending per capita (US$) Share of spending (%) Global Health Expenditure Database reports total PHC spending data but no disaggregation by financial source (ie government, external, and private [Bosnia and Herzegovina, Democratic Republic of Congo, Ethiopia, Ghana, and Uruguay]). Only five high-income countries report external funding for PHC (Barbados, Mauritius, Seychelles, St Kitts and Nevis, and Trinidad and Tobago). For other high-income countries external spending is negligible or zero. Averages are unweighted means across countries. To calculate the average of ratios, we calculated the ratio for each country and took the average for each income group. The sum of government, external, and out-of-pocket spending will not be equal to the total spending due to the omission of other types of private spending, such as voluntary private insurance.
The gap is bigger in high-income countries because private insurance is more common in high-income countries. Although out-of-pocket spending on PHC is available in the OECD database, WHO only reports domestic private spending on PHC. To estimate the out-of-pocket spending for PHC in low-income to middle-income countries, we took the ratio of total out-of-pocket spending on health to total domestic private spending on health and multiplied it by private spending for PHC for each country. (Total) Domestic Total PHC Domestic Out-of- External PHC Domestic Domestic Domestic Out-of- External Current general spending general pocket spending spending as a general general general pocket spending on health government government spending on on PHC share of government government government spending PHC as a spending expenditure spending on PHC current spending on spending on spending on on PHC as a share of on health PHC health PHC as a PHC as a PHC as a share share of total PHC spending share of share of GDP of domestic total PHC spending total PHC general spending spending government expenditure on health Low-income 40 (n=16) 8 (n=16) 24 (n=16) 3 (n=14) 12 (n=14) 8 (n=14) 59% (n=16) 13% (n=14) <1% (n=14) 33% (n=14) 44% (n=14) 35% (n=14) group Lower-middle- 104 (n=25) 44 (n=25) 52 (n=25) 16 (n=24) 23 (n=24) 8 (n=24) 52% (n=25) 29% (n=24) <1% (n=24) 36% (n=24) 49% (n=24) 14% (n=24) income group Upper-middle- 416 (n=20) 242 (n=20) 169 (n=20) 73 (n=19) 65 (n=19) 6 (n=19) 42% (n=20) 45% (n=19) 1% (n=19) 34% (n=19) 39% (n=19) 5%(n=19) income group High-income 3310 (n=34) 2355 (n=34) 1312 (n=34) 840 (n=33) 318 (n=33) 0 (n=33) 42% (n=34) 59% (n=33) 2% (n=33) 36% (n=33) 28% (n=33) <1% (n=33) group Total 1306 (n=95) 907 (n=95) 523 (n=95) 328 (n=90) 139 (n=90) 5 (n=90) 48% (n=95) 41% (n=90) 1% (n=90) 35% (n=90) 39% (n=90) 10% (n=90) GDP=gross domestic product.
Individuals with varying levels of admixture contributed samples to this dataset -from those whose grandparents reside on the same island, to individuals who describe themselves as broadly Sama in ancestry but whose ancestors originate from different islands, to those with multiple ethnicities in their family tree. Our approach is to explore ways data can be arbitrarily grouped and examine which sets more faithfully mirror genetic clusters. We further support the recommendation to use endonyms or self-applied group names in publications, or in cases when the complete consensus among the group is lacking, the use of neutral exonyms provided with explanatory notes (Max Planck Institute for Evolutionary Anthropology, 2021). Upon returning to the field sites, the research team will work with local partners to increase the communities' understanding of what science can and cannot explain.
Diverse sectoral appreciation of the Indigenous peoples' ownership of their samples and associated data The ownership of biological samples and the derived genetic information is an integral component of the informed consent of human participants in a research study. However, Indigenous peoples, many of whom are socially and economically vulnerable, are not familiar with the process and may have unknowingly provided broad consent for their samples to be used and stored in local and global databases. While data sharing, rapidly publishing results, and follow-up investigations are essential to advance the field, broad consent and unrestricted access to genomic data is counter to the Indigenous peoples' autonomy over their genomic data  (Garrison et al. , 2019)  and excludes communities from sharing in potential benefits  (Tsosie et al.
Acknowledgments We thank  Abdulaziz M. Joe  and  Madkie A. Biste  of the Office for  Southern Cultural Communities (OSCC) as well as Former Director Henrico L. Gumibao, Former Director Atty. Pinky Grace P. Pareja, OIC Director Mercilyn B. Hatad, Atty. Gibran Abubakar , and  Engr. George T. Jocutan  of the  National Commission on Indigenous Peoples-Region IX. We also acknowledge our partnership with the  Mindanao State University-Tawi-Tawi College of Oceanography and Technology (MSU-TCTO)  through  Chancellor Mary Joyce Guinto-Sali ,  Prof. Mucha-Shim L. Quiling ,  Prof. Abdul Jim J. Hassan , and  Sitti Zayda B. Halun. Our  fieldwork team was composed of  Isnaji K. Nurlaji  ( OSCC-Tawi-Tawi ),  Faizal Dawamie  ( OSCC-Sulu ),  Farhanie Bernardo ,  Thelma Alman ,  Jhay Sakandal ,  Winnie Perian ,  Richard Pamaran ,  Czarina Mae M.
No distinction based on their ages was made. All the participants worked in private practice in order to obtain a group that performed equivalent activity. The fieldwork was carried out between 2012 and 2015. Participants were selected through: (1) internet search: by using keywords in Google or searching on the websites of professional associations, (2) researcher networks: contacts were made through people from the social circle of researchers, (3) "snowball sampling": participants put researchers in touch with other dieticians. The participants were contacted by e-mail or telephone. We explained the study to them and checked their availability. Fifteen dieticians were interviewed in each country. The sample size was determined based on the method of saturation, which is when data collected becomes redundant, and no new information is obtained  37.
Traditionally, the influence of visual design and illustration has been most pronounced. This is true for the representation of complex biological objects, e. g. , membranes  [23] , cells  [24]  and pathogens  [25]. A recurring theme related to the visualization of complex biological objects is the development of appropriate abstractions. Valuable concepts have emerged in this context, such as continuous abstraction  [26]  and simplification of the shapes of molecular surfaces  [27]. Work on the concept of abstracted molecular surfaces continues in various scientific projects. A recent example are the resources for peripheral proteinmembrane interactions developed by the Reuter group in Norway (https://reuter-group. github. io/peprmint/). A final example of the transfer of design concepts to biology is exploded views.
Critical discussion In this critical discussion, we will compare our findings with the existing literature. For exploded views following the corresponding approach in mechanical drawing, we are only aware of the recent work of Sbardellati et al. [30] , which provides a very thorough and detailed analysis, while our focus is on abstracting the hull and generalizing the approach to large structural databases. The 2D imaging of the surface by unrolling that we present complements the numerous works on synthetic 2D map-like representations of molecules such as  [36]  or  [34]  by its unconventional implementation that mimics the physical process of a 360-degree photo camera. It is very simple compared to what has been described in the literature for more than 35 years  [32]  and serves more to illustrate how a design idea can be directly translated into a simple visualization tool than to offer new insights into such a mapping.
Designing proteins for a broad audience, the Top of the Prots experiment Top of the Prots (https://topoftheprots. com/) is a French blog that publishes a short post (about 600 words) each week about a particular protein of interest. Each post includes both scientific, "serious" images of proteins created with classic VMD software  [38]  (see Supplementary Figure  S5a ) and comic-style illustrations showing proteins as humorous characters, according to rule #4 for drawing scientific comics  [39] : characters can improve engagement. Relying on rule No. 1 (i. e. , you do not have to be good at art), the authors optimistically provided their own drawings to illustrate the blog (see Supplementary Fig. S5b ). When the blog was to be turned into a popular science book, it became clear that the illustrations should be redesigned by a more professional hand.
Examples of implementing design ideas into a scientific workflow A fundamental question that arose in the experiments described in the previous section is how to capture the creative know-how of the designer. It cannot simply be digitized to make it available in computerized tools and software. Nevertheless, some examples are documented in the literature, and without claiming to be exhaustive, we would like to mention here, for example, the tools MolScript  [43]  for detailed and schematic representations of protein structures, ProteinShader  [44]  for illustrative rendering of macromolecules, the software Illustrate for biomolecular illustrations  [45]  and Cellpaint  [46]  (https://ccsb. scripps. edu/cellpaint/), which enables to draw cellular landscapes using Goodsell-like biomolecular representations.
For our own experiments, we have implemented prototypes in UnityMol  [47] , or developed simple generic scripts that work with a variety of programs. As an example, Figure  7 (a) shows an experiment to represent molecular motion in still images. With this in mind, we turned some of the ideas from Chapter 3 into tool prototype implementations. For example, rolling out the 3D structure for an overview is relatively easy to implement as a camera motion that captures the corresponding images as they are rotated and stitched together as a panorama. The resulting 2D view of the GLIC ion channel surface can be seen in Figure  7 (b). In the second example, we extended the previous prototype for exploded views implemented in UnityMol  [28, 29]  by abstracting the molecular objects in a systematic way and generalizing criteria for their dissection, which is detailed in Supplementary material.
In these three implementations, domain scientists have tried to translate the designers' ideas into tools or to capture artistic originality through specific procedures. Ideally, if the designer himself could make this transfer, one might expect higher fidelity to the original idea. To facilitate such self-implementation by designers and illustrators, generative design can be an excellent approach. In generative design, the visual idea is not implemented by hand or with the digital processes that now replace the earlier Illustrator tools. Instead, it is rewritten into a set of rules and then programmed. Processing, a fairly simple graphics-oriented programming software  [48] , is an established framework for such an approach. With a few lines of code, you can obtain interactive images, modify them, and create visual effects based on "rules" established by the designer that determine the behaviour of the software.