What Do We Know about Mineral Resource Rent Sharing in Africa?

taxation; mineral tax; resource rent tax; developing countries.Governments that lack the capacity to mine resources themselves have to attract foreign direct investment. However, since resources are not renewable countries need to capture a ‘fair’ share of mineral resource rent to promote their development. While the sharp rise of the world prices of most minerals (in particular, gold, copper, iron and bauxite) multiplied the global turnover of the mining sector by 4.6 between 2002 and 2010, tax revenue earned by African governments from the non-renewable natural resource sector only grew by a factor of 1.15 (Mansour 2014). The sharing of mineral resource rent between governments and investors is often criticised for being unfavourable to African governments. But what do we really know about the sharing of mineral resource rent in Africa? The aim of this study is to review theoretical and empirical studies on rent sharing in Africa, and to note their limitations regarding knowledge of the actual sharing of mineral rent.DfID, NORA

La transgression dans Dracula de Stoker et Frankenstein de Shelley : infection du corps et de l'esprit humains

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal.[À l'origine dans / Was originally part of : Thèses et mémoires - FAS - Département de littérature comparée]Ce mémoire est une analyse comparative de Frankenstein de Mary Shelley et de Dracula de Bram Stoker sur la question de la transgression des limites naturelles et sociales. Ces deux auteurs utilisent la figure du monstre pour représenter l'importance du maintien de l'ordre pour la société et l'humain. Le monstre présente d'abord une transgression d'ordre naturel au moment de sa création qui le fait passer de la mort à la vie. Ensuite, le corps du monstre représente lui-même une transgression en étant à la fois mort, vivant, animal et humain. La présence du monstre est elle aussi une transgression, puisqu'il représente l'extériorisation d'une partie cachée de la psyché humaine. Enfin, en étant catégorisé étranger, le monstre n'a pas à respecter les lois sociales, ce qui augmente le désordre que la société doit éradiquer si elle veut survivre.This memoire is a comparative analysis of Mary Shelley's Frankenstein and Bram Stoker's Dracula on the subject of transgression. It explores the ways in which each author uses the figure of the monster to represent the transgression of limits that have been established by society and nature. The monster transgresses the limits imposed by nature at the moment of its creation and by its composition. Its body is also at the frontiers of the possible and the impossible by being simultaneously a representation of life, death, humanity and bestiality. The presence of the monster is also a transgression in itself as it is the embodiment of a part of the human psyche. Finally, the monstrous being's actions categorize him as an outsider and thus, it feels no need to respect the laws imposed on humanity by society. Order must then be re-established for humanity to survive

La fiscalité minière en Afrique : un état des lieux du secteur de l’or dans 14 pays de 1980 à 2015

The lack of information about the mining resource rent sharing between governments and investors is an easy statement in Africa. Existing public databases are often insufficient for a deep analysis of the African tax law applied to natural resource sectors, which limits the academic and operational work. The FERDI publishes the first tax and legal database which specifies the tax regime applied to industrial gold mining companies in 14 African countries from the 1980s to 2015. The database featuring three major innovations: (i) an inventory of taxes and duties (rate, base and exemptions) payable during the prospecting phase and mining phase of a gold mining project; (ii) an entirely new level of historical depth; (iii) the link between each piece of tax information and its legal source. This database is used to make a first analysis of tax regimes and rent sharing in gold producer countries. The first results emphasize heterogeneity of tax regimes between English-speaking and French-speaking countries with a convergence of the average effective tax rates that increase in most countries following the tax reforms undertaken since 2010

La fiscalité minière en Afrique : quelle évolution récente en 2018 ?

The extractive sector is of primary importance to African states. Of the 54 countries on the continent, 20 are considered by the International Monetary Fund (IMF) to be rich in natural resources. These are countries whose natural resources account for more than 25 per cent of total exports. All are sub-Saharan African countries: seven export mainly oil and gas, and 13 export mainly minerals: mostly gold, diamonds and precious stones. The significant weight of the extractive sector in these states raises the question of the taxation of these natural resources, which are non-renewable. An innovative database on the taxation of mining industries in Africa has been put online on the Ferdi website, in partnership with Cerdi and ICTD. This database covers 21 sub-Saharan African countries over a period that varies according to the availability of information in each country but can go back to the 1980s. It was created based on the tax legislation and regulations of each country, essentially the income tax acts, finance acts and mining acts. It separates the general regime (applicable to all companies) from the mining regime (applicable only to holders of mineral rights for prospecting or exploitation on an industrial scale). It focuses on a single ore: gold.Le secteur extractif est de première importance pour les Etats africains. Sur les 54 pays que compte le continent, 20 sont considérés comme riches en ressources naturelles par le Fonds Monétaire International (FMI)1. Il s’agit des pays dont les ressources naturelles représentent plus de 25% des exportations totales. Tous sont des pays d’Afrique sub-saharienne : 7 exportent principalement du pétrole et du gaz, 13 exportent principalement des minerais : surtout de l’or, des diamants et des pierres précieuses. Le poids conséquent du secteur extractif dans ces Etats pose la question de la taxation de ces ressources naturelles qui sont non-renouvelables. Une base de données inédite sur la fiscalité des industries minières en Afrique a été mise en ligne sur le site de la Ferdi, en partenariat avec le Cerdi et l’ICTD. Cette base de données couvre 21 pays d’Afrique sub-saharienne sur une période qui varie selon la disponibilité de l’information dans chaque pays mais peut remonter jusque dans les années 1980. Elle a été constituée à partir de la législation et de la réglementation fiscale de chaque pays, essentiellement les codes généraux des impôts, les lois de finances, les codes miniers et leurs textes d’application. Elle distingue le régime général (applicable à toutes les entreprises) du régime minier (applicable aux seuls titulaires de titres miniers de recherche ou d’exploitation à l’échelle industrielle). Elle se concentre sur un seul minerai : l’or

AgroFIMS v.1.0 - User manual

The Agronomy Field Information Management System (AgroFIMS) has been developed on CGIAR’s HIDAP (Highly Interactive Data Analysis Platform) created by CGIAR’s International Potato Center, CIP. AgroFIMS draws fully on ontologies, particularly the Agronomy Ontology (AgrO)1. It consists of modules that represent the typical cycle of operations in agronomic trial management (seeding, weeding, fertilization, harvest, and more) and enables the creation of data collection sheets using the same ontology-based set of variables, terminology, units and protocols. AgroFIMS therefore enables a priori harmonization with metadata and data interoperability standards and adherence to the FAIR Data Principles essential for data reuse and increasingly, for compliance with funder mandates - without any extra work for researchers. AgroFIMS is therefore of value to anyone (scientist, researcher, agronomist, etc.) who wishes to easily design a standards-compliant agronomic research fieldbook following the FAIR Data Principles. AgroFIMS also allows users to collect data electronically in the field, thereby reducing errors. Currently this is restricted to the KDSmart Android platform, but we expect to enable this capability with other platforms such as the Open Data Kit (ODK) and Field Book in v.2.0. Once data is collected using KDSmart, the data can be uploaded back to AgroFIMS for data validation, statistical analysis, and the generation of statistical analysis reports. V.2.0 will allow easy upload of the data from AgroFIMS to an institutional or compliant repository of the user’s choice

Defined plant extracts can protect human cells against combined xenobiotic effects

<p>Abstract</p> <p>Background</p> <p>Pollutants representative of common environmental contaminants induce intracellular toxicity in human cells, which is generally amplified in combinations. We wanted to test the common pathways of intoxication and detoxification in human embryonic and liver cell lines. We used various pollutants such as Roundup residues, Bisphenol-A and Atrazine, and five precise medicinal plant extracts called Circ1, Dig1, Dig2, Sp1, and Uro1 in order to understand whether specific molecular actions took place or not.</p> <p>Methods</p> <p>Kidney and liver are major detoxification organs. We have studied embryonic kidney and hepatic human cell lines E293 and HepG2. The intoxication was induced on the one hand by a formulation of one of the most common herbicides worldwide, Roundup 450 GT+ (glyphosate and specific adjuvants), and on the other hand by a mixture of Bisphenol-A and Atrazine, all found in surface waters, feed and food. The prevention and curative effects of plant extracts were also measured on mitochondrial succinate dehydrogenase activity, on the entry of radiolabelled glyphosate (in Roundup) in cells, and on cytochromes P450 1A2 and 3A4 as well as glutathione-S-transferase.</p> <p>Results</p> <p>Clear toxicities of pollutants were observed on both cell lines at very low sub-agricultural dilutions. The prevention of such phenomena took place within 48 h with the plant extracts tested, with success rates ranging between 25-34% for the E293 intoxicated by Roundup, and surprisingly up to 71% for the HepG2. By contrast, after intoxication, no plant extract was capable of restoring E293 viability within 48 h, however, two medicinal plant combinations did restore the Bisphenol-A/Atrazine intoxicated HepG2 up to 24-28%. The analysis of underlying mechanisms revealed that plant extracts were not capable of preventing radiolabelled glyphosate from entering cells; however Dig2 did restore the CYP1A2 activity disrupted by Roundup, and had only a mild preventive effect on the CYP3A4, and no effect on the glutathione S-transferase.</p> <p>Conclusions</p> <p>Environmental pollutants have intracellular effects that can be prevented, or cured in part, by precise medicinal plant extracts in two human cell lines. This appears to be mediated at least in part by the cytochromes P450 modulation.</p

AgroFIMS v.2.0 - User manual.

This documentation provides instructions to help you get familiarized with the Agronomy Field Information Management System (AgroFIMS) and to produce a fieldbook that you can use to collect well-described, standards-compliant data in the field. AgroFIMS allows users to create fieldbooks to collect agronomic data. The fieldbook is already tied to a metadata standard (the CG Core Metadata Schema, aligned with the industry standard Dublin Core Metadata Schema and required by CGIAR and many other repositories). The data variables and protocol parameters in AgroFIMS fieldbooks align with semantic standards like the Agronomy Ontology (AgrO). This a priori compliance with data standards facilitates data to be Findable, Accessible, Interoperable, and Reusable (FAIR) at collection, making it easier to interpret and aggregate. Data collection is currently available via the Android-based KDSmart or Field Book applications, and the collected data can be imported back to AgroFIMS for statistical analysis and reports. By mid-2021 you will be able to easily upload this collected data through AgroFIMS to a Dublin Core or CG Core-compliant Dataverse repository. To enable access, exchange, and integration of agronomic data across systems and applications we have made available the Agronomy API or AgrAPI, which is a RESTful web service API specification. The AgrAPI blueprint can be implemented in different programming languages, but is currently implemented in the R statistical programming language, allowing you to analyze your data with the R packages and graphics of your choice

AgroFIMS: A tool to enable digital collection of standards-compliant FAIR data

Agricultural research has been traditionally driven by linear approaches dictated by hypothesis-testing. With the advent of powerful data science capabilities, predictive, empirical approaches are possible that operate over large data pools to discern patterns. Such data pools need to contain well-described, machine-interpretable, and openly available data (represented by high-scoring Findable, Accessible, Interoperable, and Reusable—or FAIR—resources). CGIAR's Platform for Big Data in Agriculture has developed several solutions to help researchers generate open and FAIR outputs, determine their FAIRness in quantitative terms1, and to create high-value data products drawing on these outputs. By accelerating the speed and efficiency of research, these approaches facilitate innovation, allowing the agricultural sector to respond agilely to farmer challenges. In this paper, we describe the Agronomy Field Information Management System or AgroFIMS, a web-based, open-source tool that helps generate data that is “born FAIRer” by addressing data interoperability to enable aggregation and easier value derivation from data. Although license choice to determine accessibility is at the discretion of the user, AgroFIMS provides consistent and rich metadata helping users more easily comply with institutional, founder and publisher FAIR mandates. The tool enables the creation of fieldbooks through a user-friendly interface that allows the entry of metadata tied to the Dublin Core standard schema, and trial details via picklists or autocomplete that are based on semantic standards like the Agronomy Ontology (AgrO). Choices are organized by field operations or measurements of relevance to an agronomist, with specific terms drawn from ontologies. Once the user has stepped through required fields and desired modules to describe their trial management practices and measurement parameters, they can download the fieldbook to use as a standalone Excel-driven file, or employ via free Android-based KDSmart, Fieldbook, or ODK applications for digital data collection. Collected data can be imported back to AgroFIMS for statistical analysis and reports. Development plans for 2021 include new features such ability to clone fieldbooks and the creation of agronomic questionnaires. AgroFIMS will also allow archiving of FAIR data after collection and analysis from a database and to repository platforms for wider sharing