Enset in North Omo Region
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Districts of Ethiopia
Region District or Woredas Zone Remarks Afar Region Argobba Special Woreda -- Independent district/woredas Afar Region Afambo Zone 1 (Awsi Rasu) Afar Region Asayita Zone 1 (Awsi Rasu) Afar Region Chifra Zone 1 (Awsi Rasu) Afar Region Dubti Zone 1 (Awsi Rasu) Afar Region Elidar Zone 1 (Awsi Rasu) Afar Region Kori Zone 1 (Awsi Rasu) Afar Region Mille Zone 1 (Awsi Rasu) Afar Region Abala Zone 2 (Kilbet Rasu) Afar Region Afdera Zone 2 (Kilbet Rasu) Afar Region Berhale Zone 2 (Kilbet Rasu) Afar Region Dallol Zone 2 (Kilbet Rasu) Afar Region Erebti Zone 2 (Kilbet Rasu) Afar Region Koneba Zone 2 (Kilbet Rasu) Afar Region Megale Zone 2 (Kilbet Rasu) Afar Region Amibara Zone 3 (Gabi Rasu) Afar Region Awash Fentale Zone 3 (Gabi Rasu) Afar Region Bure Mudaytu Zone 3 (Gabi Rasu) Afar Region Dulecha Zone 3 (Gabi Rasu) Afar Region Gewane Zone 3 (Gabi Rasu) Afar Region Aura Zone 4 (Fantena Rasu) Afar Region Ewa Zone 4 (Fantena Rasu) Afar Region Gulina Zone 4 (Fantena Rasu) Afar Region Teru Zone 4 (Fantena Rasu) Afar Region Yalo Zone 4 (Fantena Rasu) Afar Region Dalifage (formerly known as Artuma) Zone 5 (Hari Rasu) Afar Region Dewe Zone 5 (Hari Rasu) Afar Region Hadele Ele (formerly known as Fursi) Zone 5 (Hari Rasu) Afar Region Simurobi Gele'alo Zone 5 (Hari Rasu) Afar Region Telalak Zone 5 (Hari Rasu) Amhara Region Achefer -- Defunct district/woredas Amhara Region Angolalla Terana Asagirt -- Defunct district/woredas Amhara Region Artuma Fursina Jile -- Defunct district/woredas Amhara Region Banja -- Defunct district/woredas Amhara Region Belessa -- -
Revisiting Gamo: Linguists’ Classification Versus Self Identification of the Community
Vol. 5(9), pp. 373-380, December, 2013 DOI: 10.5897/IJSA2013.0471 International Journal of Sociology and ISSN 2006- 988x © 2013 Academic Journals Anthropology http://www.academicjournals.org/IJSA Full Length Research Paper Revisiting Gamo: Linguists’ classification versus self identification of the community Hirut Woldemariam Department of Linguistics, Institute of Language Studies, Addis Ababa University, P. O. Box 1176, Addis Ababa, Ethiopia. Accepted 17 September, 2013 This study attempts to contribute to our knowledge about Gamo, a member of the North Ometo subgroup, which is one of the four subgroups that constitute the Ometo group of the Omotic language family (Fleming, 1976; Bender, 2000). This paper characterizes some of the issues in the research of language and identity. It will attempt to employ the complementary perspectives of sameness and difference between Gamo, its sisters in the North Ometo sub-branch and its dialects. North Ometo comprises of several related languages and dialects of which Gamo is one. The exact relationship amongst the Ometo languages is not well known. Not equally well known is the relationship Gamo has with its sisters and daughters. The study tries to address issues concerning with misrepresentation of the Gamo language by the existing classification in one hand and what the self perception of the Gamo community likes on the other hand. This study aimed at examining linguistic facts and the Gamo speakers’ own understandings of their identities. To this end, the study has used linguistic, anthropological and sociolinguists attempt to characterize membership of Gamo based on linguistic facts and members’ self ethno-linguistic identificationi. -
Nutrition Surveys 1999
NUTRITION SURVEYS 1999 – 2000 Region/Zone woreda Date of Agency Sample size Methodology Nutrition Indicatorsi survey Tigre throughout August SCF-UK 937 30 cluster Mean WHL <80%WFL W/H<-2 Z score W/H <-3 Z score 1999 92.8% 5.5% 7.7 % 1.0% Tigre Feb 2000 WVI W/H <-2 Z score W/H <-3 Z score Eastern May 2000 Feb 2000 May 2000 Feb 2000 May 2000 Asti Wenberta 685 13.1% 10.9% NA 2.6% Saesi Tsaedaemba 1412 22.3% 20.1% 3.7% 4.4% Amhara: May-June SCF-UK + 2900 58 clusters in Mean WFL < 80% WFL N.Wello Bugna 1999 worst drought 88.8% 4% Wadla affected woredas. 89,4% 7% Gidan 87.8% 3% Delanta Dawnt 89.4% 7% Gubalafto 90.0% 7% S. Wello Dessie Zuria 89.8% 7% Tenta 90.5% 3% Legambo 90.8% 5% Ambassel 90.7% 6% Mekdella 91.2% 4% Wag Hamra Dehana 88.2% 4% Oromyia Chefa 92.8% 2% Amhara Aug - Oct SCF-UK + 2500 50 clusters in Mean WFL < 80% WFL 1999 worst drought Aug Sept Oct Aug Sept Oct N.Wello Bugna affected woredas. 91.2% 88.7% 89.7% 6.6% 10.6% 7.0% Wadla 91.1% 90.7% 90.6% 7.3% 5.5% 5.7% Gidan 88.4% 88.2% 88.4% 8.9% 8.2% 9.6% S. Wello Delanta Dawnt 87.5% 87.6% 87.5% 11.0% 8.0% 7.6% Dessie Zuria 91.9% 90.9% 90.1% 4.0% 6.2% 5.2% Tenta 89.2% 89.1% 88.4% 10.0% 8.3% 11.7% Legambo 89.1% 89.7% 89.6% 8.4% 6.0% 6.4% Wag Hamra Dehana 89.7% 89.5% 90.5% 8.3% 8.2% 6.4% Amhara March- May SCF-UK + 2500 50 clusters in Mean WFL < 80% WFL N.Wello 2000 worst drought March 2000 May 2000 March 2000 May 2000 Bugna affected woredas 90.1% 90.6% Wadla 90.5% 91.1% S. -
Full Length Research Article DEVELOPMENT RESEARCH
Available online at http://www.journalijdr.com International Journal of DEVELOPMENT RESEARCH ISSN: 2230-9926 International Journal of Development Research Vol. 07, Issue, 01, pp.11119-11130, January, 2017 Full Length Research Article DETERMINANTS OF RURAL HOUSEHOLDS’ VULNERABILITY TO POVERTY IN CHENCHA AND ABAYA DISTRICTS, SOUTHERN ETHIOPIA *Fassil Eshetu Abebe Department of Economics, College of Business and Economics, Arba Minch University ARTICLE INFO ABSTRACT Article History: This study primarily aimed to examine the determinants of rural households’ vulnerability to Received 27th October, 2016 poverty and to profile the households according to their level of vulnerability using Feasible Received in revised form Generalized Least Square (FGLS) and Logistic Regression analysis with the help of data collected 28th November, 2016 from a sample of 500 households in two Woredas. The general poverty line of the study area was Accepted 14th December, 2016 determined to be Birr 248 per month per adult equivalent and 29.8 percent of the population in the th Published online 30 January, 2017 study areas were found to be poor. The projected consumption percapita after the three step FGLS estimation revealed that, the incidence of vulnerability to poverty in the area was 34.2 percent and Key Words: therefore, vulnerability was more spread in the study areas than ex post poverty. Using the two Poverty, Vulnerability, vulnerability thresholds, observed poverty rate (0.298) and vulnerability of 0.5, about 28.6%, Feasible Generalized Least Square, 5.6% and 65.8% of households were highly vulnerable, low vulnerable and not vulnerable Logit Model and Ethiopia. respectively. Most importantly, from the total poor households about 81.75%, 3.25% and 15% were highly vulnerable, low vulnerable and not vulnerable respectively. -
The Case of Damot Gale District in Wolaita Zone, Ethiopia) Zegeye Paulos Borko* Department of Economics, Wolaita Sodo University, PO Box 138, Wolaita Sodo, Ethiopia
onomic c s & f E o M Borko, Int J Econ Manag Sci 2017, 6:5 l a a n n a r g u e DOI: 10.4172/2162-6359.1000450 o m J International Journal of Economics & e l n a t n S o i c t i a ISSN: 2162-6359 e n n r c e t e s n I Management Sciences Research Article Research Article Open Access Child Labor and Associated Problems (The Case of Damot Gale District in Wolaita Zone, Ethiopia) Zegeye Paulos Borko* Department of Economics, Wolaita Sodo University, PO Box 138, Wolaita Sodo, Ethiopia Abstract The study was carried out at Damot Gale district of Wolaita zone in Southern nation nationalities regional state with the main objectives to describe factors of child labor in the study area. In order to attain this objective the study made use of cross-sectional household survey data collected from 94 sample households. The data collected were analyzed and discussed by using both descriptive statistics and binary logit regression model. To this end, identifying children’s who were in child labor and those who were not in child labor; descriptive result shows that from different age category 73% of the children’s were engaged in different activity and the remaining 27% responded as they were not working. Most children’s started working below the age of 8 and major sectors of work were unpaid family work such as agriculture 58% Male and 7.24% Female and Home service 7.3% Female and 22% male. The result of the logistic regression model revealed that out of 8 variables included in the model, 4 explanatory variables were found to be significant at 1%, 5% and 10% level. -
Land Use Patterns and Its Implication for Climate Change: the Case of Gamo Gofa, Southern Ethiopia
Defaru Debebe. et al., IJSRR 2013, 2(3), 155-173 Research article Available online www.ijsrr.org ISSN: 2279–0543 International Journal of Scientific Research and Reviews Land Use Patterns and its Implication for Climate Change: The Case of Gamo Gofa, Southern Ethiopia Defaru Debebe* and Tuma Ayele Arba Minch University P.O.Box 21, Arba Minch, Ethiopia ABSTRACT Land is one of three major factors of production in classical economics (along with labor and capital) and an essential input for housing and crop production. Land use is the backbone of agriculture and it provides substantial economic and social benefits. Assessing past-to present land use patterns associated with the crop production helps to understand which climatic effects might arise due to expanding crop cultivation. This study was conducted to evaluate the land use pattern and its implication for climate change in Gamo Gofa, Southern Ethiopia. For evaluation, correlation and time series trend analysis were used. Results revealed that a significant reduction in cultivable land, which was converted into cropland and might increase deforestation and greenhouse gas emission, in turn induce climate change. The correlation between cropland and fertile (cultivable) land (r=0.22674) in 2005 improved to (r=0.75734) in 2012 indicating major shift of fertile land to cropland in seven years interval. On other side, twelve years (1987-1999 and 2000-2011) average maximum temperature difference in Gamo Gafa was increased 0.425oC with standard deviation 0.331. It is statistically significant (t =1.284, alpha=0.10) at 10% level of error. Moreover, the spatial differences in climate change are likely to imply a heterogeneous pattern of land use responses. -
Ethiopia Round 6 SDP Questionnaire
Ethiopia Round 6 SDP Questionnaire Always 001a. Your name: [NAME] Is this your name? ◯ Yes ◯ No 001b. Enter your name below. 001a = 0 Please record your name 002a = 0 Day: 002b. Record the correct date and time. Month: Year: ◯ TIGRAY ◯ AFAR ◯ AMHARA ◯ OROMIYA ◯ SOMALIE BENISHANGUL GUMZ 003a. Region ◯ ◯ S.N.N.P ◯ GAMBELA ◯ HARARI ◯ ADDIS ABABA ◯ DIRE DAWA filter_list=${this_country} ◯ NORTH WEST TIGRAY ◯ CENTRAL TIGRAY ◯ EASTERN TIGRAY ◯ SOUTHERN TIGRAY ◯ WESTERN TIGRAY ◯ MEKELE TOWN SPECIAL ◯ ZONE 1 ◯ ZONE 2 ◯ ZONE 3 ZONE 5 003b. Zone ◯ ◯ NORTH GONDAR ◯ SOUTH GONDAR ◯ NORTH WELLO ◯ SOUTH WELLO ◯ NORTH SHEWA ◯ EAST GOJAM ◯ WEST GOJAM ◯ WAG HIMRA ◯ AWI ◯ OROMIYA 1 ◯ BAHIR DAR SPECIAL ◯ WEST WELLEGA ◯ EAST WELLEGA ◯ ILU ABA BORA ◯ JIMMA ◯ WEST SHEWA ◯ NORTH SHEWA ◯ EAST SHEWA ◯ ARSI ◯ WEST HARARGE ◯ EAST HARARGE ◯ BALE ◯ SOUTH WEST SHEWA ◯ GUJI ◯ ADAMA SPECIAL ◯ WEST ARSI ◯ KELEM WELLEGA ◯ HORO GUDRU WELLEGA ◯ Shinile ◯ Jijiga ◯ Liben ◯ METEKEL ◯ ASOSA ◯ PAWE SPECIAL ◯ GURAGE ◯ HADIYA ◯ KEMBATA TIBARO ◯ SIDAMA ◯ GEDEO ◯ WOLAYITA ◯ SOUTH OMO ◯ SHEKA ◯ KEFA ◯ GAMO GOFA ◯ BENCH MAJI ◯ AMARO SPECIAL ◯ DAWURO ◯ SILTIE ◯ ALABA SPECIAL ◯ HAWASSA CITY ADMINISTRATION ◯ AGNEWAK ◯ MEJENGER ◯ HARARI ◯ AKAKI KALITY ◯ NEFAS SILK-LAFTO ◯ KOLFE KERANIYO 2 ◯ GULELE ◯ LIDETA ◯ KIRKOS-SUB CITY ◯ ARADA ◯ ADDIS KETEMA ◯ YEKA ◯ BOLE ◯ DIRE DAWA filter_list=${level1} ◯ TAHTAY ADIYABO ◯ MEDEBAY ZANA ◯ TSELEMTI ◯ SHIRE ENIDASILASE/TOWN/ ◯ AHIFEROM ◯ ADWA ◯ TAHTAY MAYCHEW ◯ NADER ADET ◯ DEGUA TEMBEN ◯ ABIYI ADI/TOWN/ ◯ ADWA/TOWN/ ◯ AXUM/TOWN/ ◯ SAESI TSADAMBA ◯ KLITE -
Damot Gale, Wolayta)
Institut National French Center of Inter Aide Centre National Agronomique Ethiopian Studies France d’Etudes Agronomiques Paris-Grignon Addis Abeba Paris Des Régions Chaudes Montpellier Agricultural and economic analysis-diagnosis of Obe Jage (Damot Gale, Wolayta) Elodie Le Gal , for obtaining the DIPLOMA OF AGRICULTURAL ENGINEERING (Master’s degree) from the Institut National Agronomique Paris-Grignon (INA P-G) Nicolas Molinier , for obtaining the DIPLOMA OF TROPICAL AGRICULTURAL ENGINEERING from the CNEARC Supervising professor : Hubert COCHET, Mireille DOSSO Training supervisor : Damien Du Portal October 2006 The study region : localisation N Awash N Nazaret Volcan Damota Shashamane Sodo Arba Minch 100 km Acknoledgements First of all, we want to thank all the farmers of Obe Jage and their families. With patience, they explained us their daily work. This report is almost completely based on their knowledge. They also welcomed us warmly, providing us an unforgettable personal experience. A wink to all their children who enlivened a lot the long interviews! We could not forget our valuable translator Damsee who worked with us during the whole period of the training. Thanks to his translating skills he made the research much easier for us, being given our level in Wolaytinia!! He kept on being available even if we worked a lot! Keing gallatos ! Ant tosimo à Arba, a strong walker who gave us a precious help even if he had a lot of problems ! In Addis Ababa, we thank the French Center of Ethiopian Studies (CFEE) and its director Gérard Prunier, who supported us for this work and during our stay in Addis Ababa. -
ETHIOPIA: FOOD Emergency Appeal N° MDRET005 GLIDE N° DR-2008-000043-ETH
ETHIOPIA: FOOD Emergency appeal n° MDRET005 GLIDE n° DR-2008-000043-ETH INSECURITY 19 August 2008 This revised Appeal seeks CHF 8,157,607 (USD 7,920,006 or EUR 5,035,560) in cash, kind or services to support the Ethiopian Red Cross Society (ERCS) to assist 76,075 beneficiaries for 6 months. CHF 300,000 (USD 288,462 or EUR 187,500) was allocated from the Federation’s Disaster Relief Emergency Fund (DREF) to support this operation. Unearmarked funds to replenish DREF are encouraged. Furthermore, this emergency operation has received bilateral contributions from ECHO, through Finnish Red Cross and Austrian Red Cross (EUR 2.7 mill) and the Austrian Development Agency (EUR 200,000). Photo Above: Food distribution in process Based on the situation, this revised appeal responds to a request from ERCS to include the population of neighbouring Damot Gale who live under the same precarious situation as the population of Damot Pulasa and to provide support to 15,215 (7,200 in Damot Gale and 8,015 households in Damot Pulasa) with the total beneficiary of 76,075 (36,000 in Damot Gale and 40,075 in Damot Pulasa). This revised appeal is intended to address emergency food and relief assistance, early recovery activities as well as improving access to safe water and hygiene promotion. This operation is expected to be implemented over 6 months time The first two months’ emergency relief assistance have already been distributed in June and July 2008 in Damot Pulasa while distribution in Damot Gale is expected to start in August 2008. -
The Abaya Geothermal Development Project
THE ABAYA GEOTHERMAL DEVELOPMENT PROJECT The Great Eye – Divine Rulers (2018) by Ms. Katrin Fridriks STAKEHOLDER ENGAGEMENT PLAN VERSION 01 July 2019 RG SEP–01: 2019 Contents LIST OF TABLES 5 LIST OF FIGURES 5 REPORT REVIEW & VERIFICATION 6 ACRONMYS 7 1 INTRODUCTION 8 1.1 Overview 8 1.2 Objectives of Stakeholder Engagement 8 1.3 Scope of Application 9 2 PROJECT DESCRIPTION 10 2.1 Project Location 10 2.2 Project Settings 10 2.3 Project Description 11 2.3.1 Abaya Prospect & RG Concession 11 2.3.2 Project /Study Area 12 2.3.3 Drilling Area 13 2.4 Impacts, Benefits 13 2.4.1 Geothermal Project Impacts 13 2.4.2 Geothermal Project Benefits 14 2.5 Project Area of Influence 14 3 NATIONAL AND INTERNATIONAL REQUIREMENTS 16 3.1 Overview 16 3.2 Policies 16 3.2.1 Environmental Policy and Strategy, 1997 16 3.2.2 Ethiopian National Policy on Women, 1993 16 3.2.3 IFC PSs on Environment and Social Sustainability (2012) 17 3.2.4 IFC Good Practice Handbook on Stakeholder Engagement 18 3.2.5 Other Relevant International Policies and Conventions 19 3.3 National Laws 20 3.3.1 The Constitution 20 3.3.2 Environmental Protection Organs, Proclamation No. 295 /2002 20 3.3.3 Environmental Impact Assessment, Proclamation No. 299 /2002 21 3.3.4 Geothermal Resource Development Proclamation No. 981 /2016 21 4 STAKEHOLDER IDENTIFICATION /MAPPING 22 4.1 Introduction 22 4.1.1 Primary Stakeholder 22 4.1.2 Secondary Stakeholder 22 4.1.3 Tertiary Stakeholder 22 4.2 Stakeholders Identification 22 2 RG SEP–01: 2019 4.2.1 Government Officials 23 4.2.2 Project Proponent 23 4.2.3 -
Folk Medicinal Use of Some Animals and Their Products in Wolaita, Southern Ethiopia
Folk Medicinal Use of Some Animals and Their Products in Wolaita, Southern Ethiopia Abenezer Wendimu Wolaita Sodo University Wondimagegnehu Tekalign ( [email protected] ) Wolaita Sodo University https://orcid.org/0000-0002-4721-7528 Research Keywords: Ethnozoology, Folk medicine, Indigenous knowledge, Traditional medicine, Zootherapy Posted Date: July 24th, 2021 DOI: https://doi.org/10.21203/rs.3.rs-733638/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/27 Abstract Background Ethiopia is endowed with a diverse set of oral and faunal resources that are useful to human beings in one or another ways. A faunal resource has played a signicant role in human life from the earliest days of recorded history for medicinal purposes to treat different ailments and is still common in many parts of the world. Methods A eld survey was carried out in Diguna Fango district from March 2021 to June 2021 by personal interviews through semi- structured questionnaires and open group discussions. Results Altogether 200 (125 male and 75 female) informants provided information regarding the therapeutic uses of different animal parts/products. A total of 39 animal parts/products used for the treatment of 159 different ailments were identied. Mammals occupied the highest use report 26(66.67%), followed by arthropods 5(12.81%) and avian species 4(10.26%). Further, some most popular zootherapeutic animals i.e. Phacochoerus africanus, Hystrix cristata, Bos taurus, Equus africanus asinus, Homo sapiens, etc. were used to treat more than three different ailments. Anemia, asthma, bone fractures, cold, evil eye, fever, pleurisy, rheumatism, skin disease, and stomach pain were some of the frequently occurring ailments. -
Demography and Health
SNNPR Southern Nations Nationalities and Peoples Demography and Health Aynalem Adugna, July 2014 www.EthioDemographyAndHealth.Org 2 SNNPR is one of the largest regions in Ethiopia, accounting for more than 10 percent of the country’s land area [1]. The mid-2008 population is estimated at nearly 16,000,000; almost a fifth of the country’s population. With less than one in tenth of its population (8.9%) living in urban areas in 2008 the region is overwhelmingly rural. "The region is divided into 13 administrative zones, 133 Woredas and 3512 Kebeles, and its capital is Awassa." [1] "The SNNPR is an extremely ethnically diverse region of Ethiopia, inhabited by more than 80 ethnic groups, of which over 45 (or 56 percent) are indigenous to the region (CSA 1996). These ethnic groups are distinguished by different languages, cultures, and socioeconomic organizations. Although none of the indigenous ethnic groups dominates the ethnic makeup of the national population, there is a considerable ethnic imbalance within the region. The largest ethnic groups in the SNNPR are the Sidama (17.6 percent), Wolayta (11.7 percent), Gurage (8.8 percent), Hadiya (8.4 percent), Selite (7.1 percent), Gamo (6.7 percent), Keffa (5.3 percent), Gedeo (4.4 percent), and Kembata (4.3 percent) …. While the Sidama are the largest ethnic group in the region, each ethnic group is numerically dominant in its respective administrative zone, and there are large minority ethnic groups in each zone. The languages spoken in the SNNPR can be classified into four linguistic families: Cushitic, Nilotic, Omotic, and Semitic.