Blavatnik School Research Articles

Modeling Adaptive Performance of the Academics in Selected Public Universities in Eastern Philippines during the COVID-19 Pandemic

The COVID-19 crisis has prompted the implementation of new measures aimed at containing the virus, given its potential health threats to humanity. Studies indicate that the stringency of these policies is associated with a country’s performance in managing the pandemic. However, the literature still needs more coherent evidence on the relationship between policy stringency, COVID-19 management, and corruption perception, and thus, warrants further investigation. This study used data mining on publicly available datasets from 96 countries worldwide, which include Transparency International’s corruption perception index, COVID-19 stringency measures from the University of Oxford’s Blavatnik School of Government, and COVID-19 management performance scores from the Lowy Institute. The researchers applied clustering techniques to group nations with similar characteristics and mediation analysis to explore the relationship between a country’s corruption perception and its COVID-19 stringency concerning its management performance. Findings revealed four clustered countries. Fourteen countries with less stringent policies and highly transparent tend to manage COVID-19-related indicators better. Thirty-six countries were imposing stricter policies with low scores in the corruption perception level inclined to have lower COVID-19 management performance. Forty-five countries with average stringency and corruption perception levels have average COVID-19 management performance. Meanwhile, the mediation results proposed no mediation effects of the corruption perception on the association of the policy severity and the COVID-19 management performance level of the 96 countries and all clustered countries. With these findings, this study hopes to enlighten policymakers to review the strictness of their policies, as it posits an inverse effect on the COVID-19 management performance of a country.

Does Oxford Government Response Tracker Explain the SARS-CoV-2 Morbidity and Mortality: An Ecological Time Series Study.

Many nations swiftly designed and executed government policies to contain the rapid rise of SARS-CoV-2 cases. The government actions can be broadly segmented as movement and mass gathering restrictions (such as travel and lockdown), public awareness (such as facial covering and hand washing), emergency healthcare investment and social welfare provisions (such as poor welfare schemes to distribute food and shelter). The Blavatnik School of Government-Oxford university tracked various policy initiatives by governments across the globe and released them as composite indices. We assessed the overall government response using Oxford Comprehensive Health Index (CHI) and Stringency Index (SI) to combat the SARS-CoV-2 pandemic. This study aims to demonstrate the utility of CHI and SI to gauge and evaluate the government responses for containing the spread of SARS-CoV-2. We expect a significant inverse relationship between policy indices (CHI and SI) and SARS-CoV-2 severity indices (morbidity and mortality). In this ecological study, we analysed data from two publicly available data sources released between March 2020, to October 2021: Oxford Covid-19 Government Response Tracker (OxCGRT) and World Health Organization (WHO). We applied Auto-Regressive Integrated Moving Average (ARIMA) and Seasonal ARIMA (SARIMA) to model the data. The performance of different models was assessed using a combination of evaluation criteria: Adj-R2, Root Mean Square of Error (RMSE) and Bayesian Information Criteria (BIC). The strict implementation of policies by the government to contain the crises of SARS-CoV-2 resulted in higher CHI and SI in the beginning. Although the value of CHI and SI gradually fell--the same was consistently higher at values of more than 80% points. During the initial investigation, we found that Cases Per Million (CPM) and Deaths Per Million (DPM) followed the same trend. However, the final CPM and DPM model were SARIMA (3,2,1)(1,0,1) and ARIMA (1,1,1), respectively. The current study does not support the hypotheses that SARS-CoV-2 severity (CPM and DPM) is associated with stringent policy measures (CHI and SI). Our study concludes that the policy measures (CHI and SI) do not explain the change in epidemiological indicators (CPM and DPM). The study reiterates our understanding that strict policies do not necessarily lead to better compliance but may overwhelm the overstretched physical health systems. The 21st-century problems, thus, demand 21st-century solutions. The digital ecosystem was instrumental in the timely collection, curation, cloud storage and data communication. Thus, digital epidemiology can--and--should be successfully integrated into existing surveillance systems for better disease monitoring, management and evaluation.

Effects of non-pharmaceutical interventions on the death rates from COVID-19 in Canada

This paper examines the effectiveness of provincially enacted policies to deter the COVID-19 mortality rate during the pre-vaccine rollout pandemic in Canada. The data has been collected from Statistics Canada and other various online resources including the Blavatnik School of Government and provincial statements. Relevant information was collected for individual provinces from 11 March 2020 to 31 Jan 2021. A two-stage least squares methodology was applied by examining, by province, the cumulative number of deaths reported as due to COVID-19 before and after policy implementation. We examine the effect of each of several policies based on a 20 plus day lagged period after being put into place. Our main finding is that workplace closures and strict gathering restrictions are associated with a decrease in mortality rates of COVID-19 in Canada. We also find that the strength of the policies overall is associated with a decrease in mortality rates of COVID-19 in Canada. Using data from the Google Mobility Report we confirm that the announcements of the policies had significant behavioural effects on individuals’ movements. We interpret that social distance policies, specifically the workplace closure and strict gathering policies, have been effective factors decreasing mortality from the Coronavirus epidemic in Canada.

Mediation Effect of Corruption Perception on COVID-19 Stringency and Management Performance

The COVID-19 crisis has prompted the implementation of new measures aimed at containing the virus, given its potential health threats to humanity. Studies indicate that the stringency of these policies is associated with a country’s performance in managing the pandemic. However, the literature still needs more coherent evidence on the relationship between policy stringency, COVID-19 management, and corruption perception, and thus, warrants further investigation. This study used data mining on publicly available datasets from 96 countries worldwide, which include Transparency International’s corruption perception index, COVID-19 stringency measures from the University of Oxford’s Blavatnik School of Government, and COVID-19 management performance scores from the Lowy Institute. The researchers applied clustering techniques to group nations with similar characteristics and mediation analysis to explore the relationship between a country’s corruption perception and its COVID-19 stringency concerning its management performance. Findings revealed four clustered countries. Fourteen countries with less stringent policies and highly transparent tend to manage COVID-19-related indicators better. Thirty-six countries were imposing stricter policies with low scores in the corruption perception level inclined to have lower COVID-19 management performance. Forty-five countries with average stringency and corruption perception levels have average COVID-19 management performance. Meanwhile, the mediation results proposed no mediation effects of the corruption perception on the association of the policy severity and the COVID-19 management performance level of the 96 countries and all clustered countries. With these findings, this study hopes to enlighten policymakers to review the strictness of their policies, as it posits an inverse effect on theCOVID-19 management performance of a country.

The policy response to COVID-19 pandemic and its impact on the equity market sentiment: The Indian experience.

We examine the dynamics of the impact of the evolving policy response during the COVID‐19 pandemic on the equity market sentiment in India. We operationalise our study by examining the India VIX, the fear gauge of the Indian equity market as an indicator for the market sentiment, and the country level Government Response Index of the Blavatnik School of Government, Oxford University as an indicator for the policy response. The relation is examined through the Markov‐switching model using high‐frequency daily data from January 30, 2020, to May 31, 2021. The evidence suggests that the policy response has a positive impact on the market sentiment when the market is fearful. Further, the evidence suggests that both the high‐fear state and the low‐fear state of the market sentiment given by the model are short‐lived indicating heightened volatility and possible speculation during the ongoing pandemic in the Indian equity market.

Pandemic Policy and Life Satisfaction in Europe.

We use data from the COME‐HERE longitudinal survey collected by the University of Luxembourg to assess the effects of the policy responses to the COVID‐19 pandemic on life satisfaction in France, Germany, Italy, Spain and Sweden over the course of 2020. Policy responses are measured by the Stringency Index and the Economic Support Index from the Blavatnik School of Government. Stringency is systematically associated with lower life satisfaction, controlling for the intensity of the pandemic itself. This stringency effect is larger for women, those with weak ties to the labor market, and in richer households. The effect of the Economic Support is never statistically different from zero.

An Ecological Study Assessing the Relationship between Public Health Policies and Severity of the COVID-19 Pandemic.

Reliance on government-led policies have heightened during the COVID-19 pandemic. Further research on the policies associated with outcomes other than mortality rates remains warranted. We aimed to determine associations between government public health policies on the severity of the COVID-19 pandemic. This ecological study including countries reporting ≥25 daily COVID-related deaths until end May 2020, utilised public data on policy indicators described by the Blavatnik school of Government. Associations between policy indicators and severity of the pandemic (mean mortality rate, time to peak, peak deaths per 100,000, cumulative deaths after peak per 100,000 and ratio of mean slope of the descending curve to mean slope of the ascending curve) were measured using Spearman rank-order tests. Analyses were stratified for age, income and region. Among 22 countries, containment policies such as school closures appeared effective in younger populations (rs = −0.620, p = 0.042) and debt/contract relief in older populations (rs = −0.743, p = 0.009) when assessing peak deaths per 100,000. In European countries, containment policies were generally associated with good outcomes. In non-European countries, school closures were associated with mostly good outcomes (rs = −0.757, p = 0.049 for mean mortality rate). In high-income countries, health system policies were generally effective, contrasting to low-income countries. Containment policies may be effective in younger populations or in high-income or European countries. Health system policies have been most effective in high-income countries.

A COVID-19 Pandemic Artificial Intelligence-Based System With Deep Learning Forecasting and Automatic Statistical Data Acquisition: Development and Implementation Study.

BackgroundMore than 79.2 million confirmed COVID-19 cases and 1.7 million deaths were caused by SARS-CoV-2; the disease was named COVID-19 by the World Health Organization. Control of the COVID-19 epidemic has become a crucial issue around the globe, but there are limited studies that investigate the global trend of the COVID-19 pandemic together with each country’s policy measures.ObjectiveWe aimed to develop an online artificial intelligence (AI) system to analyze the dynamic trend of the COVID-19 pandemic, facilitate forecasting and predictive modeling, and produce a heat map visualization of policy measures in 171 countries.MethodsThe COVID-19 Pandemic AI System (CPAIS) integrated two data sets: the data set from the Oxford COVID-19 Government Response Tracker from the Blavatnik School of Government, which is maintained by the University of Oxford, and the data set from the COVID-19 Data Repository, which was established by the Johns Hopkins University Center for Systems Science and Engineering. This study utilized four statistical and deep learning techniques for forecasting: autoregressive integrated moving average (ARIMA), feedforward neural network (FNN), multilayer perceptron (MLP) neural network, and long short-term memory (LSTM). With regard to 1-year records (ie, whole time series data), records from the last 14 days served as the validation set to evaluate the performance of the forecast, whereas earlier records served as the training set.ResultsA total of 171 countries that featured in both databases were included in the online system. The CPAIS was developed to explore variations, trends, and forecasts related to the COVID-19 pandemic across several counties. For instance, the number of confirmed monthly cases in the United States reached a local peak in July 2020 and another peak of 6,368,591 in December 2020. A dynamic heat map with policy measures depicts changes in COVID-19 measures for each country. A total of 19 measures were embedded within the three sections presented on the website, and only 4 of the 19 measures were continuous measures related to financial support or investment. Deep learning models were used to enable COVID-19 forecasting; the performances of ARIMA, FNN, and the MLP neural network were not stable because their forecast accuracy was only better than LSTM for a few countries. LSTM demonstrated the best forecast accuracy for Canada, as the root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) were 2272.551, 1501.248, and 0.2723075, respectively. ARIMA (RMSE=317.53169; MAPE=0.4641688) and FNN (RMSE=181.29894; MAPE=0.2708482) demonstrated better performance for South Korea.ConclusionsThe CPAIS collects and summarizes information about the COVID-19 pandemic and offers data visualization and deep learning–based prediction. It might be a useful reference for predicting a serious outbreak or epidemic. Moreover, the system undergoes daily updates and includes the latest information on vaccination, which may change the dynamics of the pandemic.

Correlation of Society Stringency/Openness Measures with Timely Trend of COVID-19 Cases - Case Study – Albania Versus Italy

Following the WHO declaration for COVID-19 as a pandemic, this disease has caused an international crisis with a severe impact on economic and health care systems. After the first cases reported in China, the disease has progressively widespread worldwide where all affected countries has adapted specific safety protocols and tried to find new therapies in order to face this new disease. The final objective is to evaluate the overall impact of stringency measures taken from Albanian and Italian governmental authorities in relation to daily cases of COVID-19 in each country. This is a descriptive paper where the data collected in Albania and Italy according to authority-based stringency measures were compared with their output; temporary trend of daily cases. Officially Albania reported the first COVID-19 case in 8th of March in an Albanian citizen just arrived from Italy, meanwhile in Italy the first cases dated January 31st were a Chinese couple in Rome who had travel from Wuhan City. Both governments took action by applying different closer measures; thereby Blavatnik School of Government has introduced the Oxford COVID-19 Government Response Tracker (OxCGRT) in order to quantifying numerically these actions. According to OxCGRT, Albania and Italy present similar level of stringency indicator, but epidemiological curve of daily cases is totally different in shape. Italian curve corresponds to a typical outbreak, while Albania curve seem like any endemic disease in the population. In front of this pandemic, the Albanian curve might be cut off as a result a small number of tests carried out by Albania authorities, 6906 tests/million population, which is far lower than tests performed by Italian authorities, which is 11 times fold (79908 test/million population). Toward end of May the number of COVID-19 were dropped so both governments planned to relief closure measures by opening most of public and economic activities. In front of the fear that COVID-19 could rise up again, as a result of virus transmission amongst people that was observed in Albania, while in Italy continued with the low and decreasing trend of disease cases. Data and their comparison though different indicators or index, shows that stringency measures could contribute on a temporary diminution of new cases of COVD-19, but if not are accompanied with individual protection measures, and/or special vulnerable groups it might be a missing opportunity because the general population might lose what was achieved during national quarantine. On the other hand, taking in consideration low public spending per capita in Albania (307 USD, 2014), moving from “hummer” toward “dance” phase, managing and supporting health system is critical. Public health services should be mainly the entitled authorities to monitor data and come up with specific and efficient measures in order to prevent an increase of cases on the overall population.Keywords: Albania, Italy, stringency index, epidemic, COVID-19; Pandemic;

Effects and sequencing of COVID-19 pandemic control policies in Latin America

Introduction: The extraordinary impact caused by the COVID-19 pandemic in Latin America gives special importance to the analysis of the control policies implemented. Objectives: 1) To update the evolution of the characteristics of COVID-19 control policies in Latin America, and 2) to analyze the sequence in which these policies are implemented. Methods: Data from the Government Response Stringency Index (GRSI), developed by the Blavatnik School of Government at Oxford University, was analyzed for the 20 Latin American countries in the period January 21 to November 9, 2020. The evolution of the GRSI, as well as of some of its components, was taken into account. The sequence of implementation in three countries (Uruguay, Argentina, and Panama) was also analyzed. Results: The vast majority of the region’s countries recorded an average GRSI of over 57 (out of 100) for the period. In 15 countries of the region, the mandatory closure of educational institutions was in effect on 75 % of the days. Eighteen countries implemented mandatory closures of businesses at some point. Ten countries applied requirements to remain in the home on more than 80 % of the days. The sequence of policies implemented by Uruguay reveals greater flexibility in application than those implemented by Argentina and Panama. Discussion: Uruguay’s experience shows that control of the pandemic was possible, and that differences with other countries may be related to structural (pre-pandemic) factors, and management performance. Conclusions: Health systems in the region must identify in detail the institutional constraints evident in controlling the pandemic, both to meet the challenges of health services in the coming months, and to improve preparedness for future pandemics.

ROUTLEDGE HANDBOOK OF RELIGIOUS LAWS. Edited by RossellaBottoni and SilvioFerrari. London: Routledge, 2019. Pp. ix + 371. £ 152.

Religious Studies ReviewVolume 46, Issue 4 p. 501-502 Surveying the Routledge Handbooks on Religion ROUTLEDGE HANDBOOK OF RELIGIOUS LAWS. Edited by Rossella Bottoni and Silvio Ferrari. London: Routledge, 2019. Pp. ix + 371. £ 152. Mariëtta D. C. van der Tol, Mariëtta D. C. van der Tol Blavatnik School of Government, Oxford, OX2 6GGSearch for more papers by this author Mariëtta D. C. van der Tol, Mariëtta D. C. van der Tol Blavatnik School of Government, Oxford, OX2 6GGSearch for more papers by this author First published: 09 December 2020 https://doi.org/10.1111/rsr.14888Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume46, Issue4December 2020Pages 501-502 RelatedInformation

Early Effects of Lockdown in India: Gender Gaps in Job Losses and Domestic Work.

India imposed one of the strictest lockdowns in the world to contain the spread of COVID-19 pandemic. According to the Stringency Index developed by the Blavatnik School of Government at the University of Oxford, by the 25th of March, 2020, India had already reached the highest possible level of stringency (index value = 100). This involved a near-complete shutdown of all economic activity. What were the labour market implications of this shutdown? The first-order effects are evident in the massive increase in total unemployment. However, is the pandemic and its aftermath a great leveller? Are the labour implications of the lockdown gender neutral? How did the lockdown affect domestic time allocation, in particular time spent on domestic work and with friends? Were these changes gender neutral, given that the lockdown was gender blind?

Six months of COVID-19 response in Nigeria: lessons, challenges, and way forward

Background: The declaration of COVID-19 as a public health emergency by the World Health Organization necessitated countries across the globe to implement response and mitigation measures. We aimed to assess the Nigerian government's response following six months of detection of COVID-19 in Nigeria.
 Methods: A narrative review of existing literature on the topic was done. The authors' opinion as experts supporting the COVID-19 pandemic response was included. The review and opinion were summarized, covering six months of the outbreak response in Nigeria.
 Results: Contact tracing commenced after identifying the index case of COVID-19 in Nigeria but has been faced with challenges such as inadequate equipment and shortage of funds. School closure was implemented barely three weeks after detecting the index case, but the resumption of terminal classes has been announced recently. The Nigerian government implemented restrictions on gatherings involving up to 11 people after three weeks following the detection of the index case of COVID-19. The lack of enforcement and supervision of gatherings and public events made many individuals disregard the restriction measures. Lockdowns on religious gatherings and public events have been recently eased nationwide, and regulatory measures have been put in place. The Nigerian government implemented bans on international travel from all countries, especially high-risk countries. However, the existence of porous borders limited success, which could have been obtained from the travel ban.
 Conclusion: COVID-19 mitigation measures should be implemented and reinforced as required nationwide and get provided the needed support.
 
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An Ecological Study Assessing the Relationship between Public Health Policies and Severity of the COVID-19 Pandemic

Background: The COVID-19 pandemic has claimed almost half a million deaths worldwide. Reliance on government-led policies have been heightened during the pandemic to mitigate the spread of disease. Which of these policies are associated with important outcomes other than mortality rates remains unknown. Hence, we aimed to determine the associations between government public health policies on the severity of the COVID-19 pandemic. Methods: This ecological study utilised publicly accessible data on seventeen policy indicators of Containment, Economic and Health systems and their respective Stringency Index described by the Blavatnik school of Government. Countries reporting >25 daily COVID-related deaths until end May 2020 were included. We assessed the association of individual SI with the profile of severity of COVID-19 by using several outcomes; mean mortality rate, time to peak, peak deaths per 100,000 population, cumulative deaths after peak per 100,000 population and ratio of the mean slope of the descending curve to the mean slope of the ascending curve. Analyses were stratified according to age, income and region. Spearman rank-order tests were employed to measure associations. Results were presented descriptively and direct comparisons were made. Findings: Twenty-two countries were included. Containment policies appeared more effective in younger populations and debt/contract relief in older populations. In European countries, containment policies were generally associated with good outcomes. In non-European countries, school closures alone had the strongest association with most of the outcomes examined. In high-income countries, health system policies such as public information campaigns and testing were generally effective, in contrast to low-income countries. Interpretation: Containment policies may be effective when targeted towards younger populations and occur in high-income or European countries. Health system policies have not been as effective in low-income and non-European countries.Funding Statement: None.Declaration of Interests: None.Ethics Approval Statement: Due to the ecological study design and the use of publicly accessible data, ethical approval was not required.

Analysing Covid-19 Epidemic Trajectories: are Countries Flattening the Curve?

Introduction: We evaluated COVID19 epidemic trajectories of different countries in terms of relative trajectory steepness and anticipated epidemic duration, in other words “flatness of the curve”. Methods: We used open-domain data on COVID-19 reported cases and deaths per country per day. A subset of 47 countries was analysed. Data were fitted with an analytical model following Gompertz equation. Uncertainty pertaining to the model forecasts was also quantified. To relate differences in epidemic trajectories of different countries to the mitigation approach taken by governments of those countries, we made use of the COVID-19 Government Response Stringency Index developed and published by Oxford University and Blavatnik School. Results: Acceptable quality fits were obtained for all the countries with R2 mostly in excess of 0.98. Uncertainty on the final Cases and/or Deaths count is typically a factor of two early in the epidemic but this quickly reduces as the epidemic progresses. Uncertainty on Epidemic Duration also reduces but less fast. Statistics on key parameters like Epidemic Duration, Epidemic Peak and Final Mortality Rate were obtained and then cross-correlated with the rigor of government measures as recorded in the Stringency Score. Most significantly, we find a clear trend of decreasing Peak Epidemic height (and to a less extent, shorter Epidemic Duration) with increased Government Stringency at the epidemic onset. We also find that Final Mortality Rate decreases with increased Stringency of Government Testing and Contact-Tracing. Conclusions: Whilst COVID-19 epidemic trajectories for most countries are similar, some countries do have flatter and less severe trajectories than others. Our analysis suggests that mitigation measures taken by a government at the very initial stage of a COVID-19 outbreak might significantly impact severity and to a less extent duration of the epidemic.

COVID-19 & Quarantine Measures: A Comparison between India & Russia

The Governments of the different countries are taking a wide range of measures in response to the COVID-19 outbreak. For assessing the rigour of quarantine measures, the Blavatnik School of Government at the University of Oxford has launched the world`s first COVID-19 government response tracker—the Oxford Coronavirus Government Response Tracker – OxCGRT). This tool aims to track and compare policy responses of governments around the world, rigorously and consistently. According to the COVID-19 Government Response Stringency Index (GRSI) the strictest measures are in India (97.37 points) and less stringent ones are in the Russian Federation (63.89 points). The study compares restrictive measures in India and Russia, analyses their impact on the spread of COVID-19; and estimates mortality rates. Besides, the study also probes population coverage aimed at diagnosing through the use of testing methods and possible economic consequences of quarantine measures.

Government Measures and Economic Activity during the COVID-19 Outbreak: Some Preliminary Short-Term Evidence from Europe

The coronavIrus Disease 19 (COVID-19) outbreak has resulted in a major worldwide economic depression. Governmental reactions to face the COVID-19 pandemic threat are varied and characterised by diverse intensity. Restrictive measure have been taken to control the pandemic, although the same actions have determined economic fallouts that need to be faced by additional measures of social welfare support. The question concerning the type and the intensity of the governmental actions is still an open issue in the public debate. The present contribution is aimed at offering evidence on the impact of anti-COVID government actions on the volume of trade. Using monthly Eurostat data on 29 European countries, it investigates the relationship between the turnover of volume of sales (the percentage change on previous period) and the adoption of governmental measures. Explanatory variables employed encompass the government response to COVID-19 pandemic as measured by the Oxford University team led by the Blavatnik School of Government, namely, a government response index, a stringency index, a containment and health index and an economic support index. Among control variables used, there is an indicator of consumer confidence. It has been estimated a generalised least squares model, controlling for heteroskedasticity across panels and autocorrelation. The results outlined a positive relationship between consumer confidence and the percentage change of the index of deflated turnover of retail sale of food, beverages and tobacco; a negative relation between restrictive governmental measures; a negative relation between consumer confidence and the percentage change of the index of deflated turnover of retail sale via mail order houses or Internet. Instead, it emerged a positive relation between governmental measures aimed at stringency and the percentage change on previous period of the index of deflated turnover of retail sale via internet. The positive impact on internet retail outlines the growing importance of this channel for trade.

META‐REGULATION IN PRACTICE: BEYOND NORMATIVE VIEWS OF MORALITY AND RATIONALITY. F.C. Simon. London and New York: Routledge, 2017.

Australian Journal of Public AdministrationVolume 78, Issue 1 p. 123-124 BOOK REVIEW META-REGULATION IN PRACTICE: BEYOND NORMATIVE VIEWS OF MORALITY AND RATIONALITY. Simon, F.C.. London and New York: Routledge, 2017. Christopher Hood, Visiting Professor, Blavatnik School of Government, Oxford, UKSearch for more papers by this author Christopher Hood, Visiting Professor, Blavatnik School of Government, Oxford, UKSearch for more papers by this author First published: 14 December 2018 https://doi.org/10.1111/1467-8500.12362Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat Volume78, Issue1March 2019Pages 123-124 RelatedInformation

Clustering of medieval scripts through computer image analysis: Towards an evaluation protocol

This paper addresses the question of objective categories of medieval scripts and their elaboration through both medieval palaeography and image analysis. It introduces a dataset of 9800 images and metadata from the catalogues of dated manuscripts in France, as a ground truth and evaluation protocol, to be used for image feature analysis, taxonomy building, and clustering methods. It further compares the results of the categorization performed by two teams, one in Lyon (LIRIS/INSA, Frank Lebourgeois) and the other in Tel-Aviv (The Blavatnik School of Computer Science at Tel Aviv University, Lior Wolf). It also addresses the questions of taxonomy, interpretation and goals of the interdisciplinary research, such as development of expert systems or exploratory research.

Africa: New Opportunities, Old Impediments

Economic AffairsVolume 35, Issue 2 p. 169-177 The 2014 Harold Wincott Memorial Lecture Africa: New Opportunities, Old Impediments Paul Collier, Paul Collier Professor of Economics and Public Policy, Director, Co-Director paul.collier@economics.ox.ac.uk Blavatnik School of Government, University of Oxford International Growth Centre Centre for the Study of African EconomiesThis lecture was delivered on 8 October 2014. The annual Harold Wincott Memorial Lecture is presented by the Wincott Foundation, which was set up in 1969 in honour of Harold Wincott (1906–1969), a distinguished British economic journalist.Search for more papers by this author Paul Collier, Paul Collier Professor of Economics and Public Policy, Director, Co-Director paul.collier@economics.ox.ac.uk Blavatnik School of Government, University of Oxford International Growth Centre Centre for the Study of African EconomiesThis lecture was delivered on 8 October 2014. The annual Harold Wincott Memorial Lecture is presented by the Wincott Foundation, which was set up in 1969 in honour of Harold Wincott (1906–1969), a distinguished British economic journalist.Search for more papers by this author First published: 15 June 2015 https://doi.org/10.1111/ecaf.12119Citations: 5 Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Citing Literature Volume35, Issue2June 2015Pages 169-177 RelatedInformation