The Future of Smallholder Farming in Eastern Africa - Uganda ...

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CHAPTER NINE Management Regulations and Enforcement in Malawi Fisheries E. Kaunda, D. Maliro, M. Mphepo, S. Khaila, L. Kamanga, L. Y. Phiri, and J. Valeta
Management Regulations and Enforcement in Malawi Fisheries 1.0 INTRODUCTION 1.1 Background Fisheries resources make a significant contribution to the economy of Malawi. In this country with high protein-related nutritional problems, about 70 percent of animal protein comes from fish. An estimated 70,000 households depend on the fishing industry as a major source of their livelihoods. The fisheries sector directly employs about 3,000 artisans, a good proportion of whom are female fish processors, and the collapse of the fishing industry will negatively impact these people. The major proportion of fish is supplied from Lake Malawi through capture fisheries. More than 600 fish species are caught in Lake Malawi. Most them are endemic to the lake and are not found anywhere else in the world. The preference for certain species over others can be shown by the catching effort devoted to certain fisheries. For example, Oreochromis spp., locally known as chambo, is said to command higher prices at the market than other species and therefore encourages more entrants into the chambo fishery (Turner 1996). It is also stated that the yield of chambo from the southern part of Lake Malawi and Lake Malombe has declined by almost 94 percent, from approximately 10,000 tons in the early 1980s to about 600 tons in the 1990s. Whereas the increase in catching effort due to preferential consumer demand for chambo is one possible reason for the decline of the chambo, other studies point to the failure to enforce management regulations as the major reason (GOM 1993). These reasons remain speculative, and unless real root causes, constraints, and threats are identified and opportunities for addressing these problems well spelt out, it is unlikely that the problem of diminishing chambo fishery will be arrested. Consequently, there are fears that by 2020 the chambo stocks will be completely extinct in Lake Malawi and Lake Malombe. In an attempt to address the problem of declining fishes, the Government of Malawi introduced various interventions. The major one was the Participatory Fisheries Management (PFM) Program, which aimed to improve the fishery through community enforcement of fishery management regulations. This program was introduced in 1993 after the implementation of the United Nations Development Programme (UNDP)/Food and Agriculture Organization of the United Nations (FAO) Chambo Fisheries Project (1988–92), whose findings suggested that the major cause for the chambo decline was government’s failure to enforce management regulations. The enforcement program was said to be topdown (from government to community) and lacked community participation. The PFM Program, which placed communities at the center, was seen to be the panacea to stock recovery. After about a decade of PFM, the chambo fishery did not appear to be recovering. On the contrary, the fishery was still declining. Recent literature (GOM 2003) shows that total fish landings declined from about 65,000 metric tons4 a year in the 1970s and 1980s to 50,000 tons a year in the late 1990s. The decline in fish catches has led to a decline in the contribution of fish to human protein intake of more than 50 percent, from a peak intake of 70 4 Hereafter all tons mentioned in this report are metric tons.
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Part One - Agricultural Productivit
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I. Introduction Agricultural Produc
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came about from expansion of cultiv
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study, therefore, limited itself to
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Land allocation and yields of 12 cr
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Table 6: Key economic variables for
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local seed in absolute terms and th
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Table 11: Crosscutting priority con
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Table 13: General constraints to ma
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These results clearly demonstrate t
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Table 18: Crosscutting constraints
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V. Policy Implications The findings
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References Appleton, Simon (2001).
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1.0 BACKGROUND 1.1 Introduction Low
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egins with a summary of the literat
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Source: National Wetlands Conservat
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shillings (§37-38). Every landowne
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Similarly, Howard (1995) used socia
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Uganda may well have more than a qu
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factors that explain household leve
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of inputs 18 , pests and diseases,
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(PMA p. 27). It also requires impro
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agriculturalists, who still do not
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to have covered 30,000 ha. During t
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4.0 RESEARCH METHODOLOGY The breadt
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• What is the current extent of w
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Figure 2. Changes in Sources of Com
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Figure 5. Proportion of Households
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estimates are remarkably consistent
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FSI - Percentage by District Distri
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was corrected using the White-Huber
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utilization for the household. Howe
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The nature of the structures to con
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impact of irrigation on horticultur
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growing population. Wetland protect
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APPENDICES Appendix 1. The Wetlands
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Appendix 2. THE 5V’s PRIORITY CLA
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Appendix 5. Determinants of Product
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Estimated covariances = 79 Number o
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International Food Policy Research
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Scherr, Sara J., 1999b. Poverty-env
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Land Tenure, Agricultural Productiv
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1.3 Statement of the problem Land s
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In order to achieve these objective
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densely populated Nyeri and Kakameg
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Figure 3: Conceptual Model Type of
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Figure 4: Location of the Study Dis
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By 2001, land demarcation and regis
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3.4 Survey Design The survey was un
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3.5.3 Model of Environmental Degrad
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questionnaire (Figure 8). Prominent
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Figure 10: Availability of hired la
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Figure 13 shows the level of cultiv
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joint significance test on the 4 dr
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Table 8: Regression Results on Maiz
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was classified into three categorie
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Table 9: Tobit Analysis with Enviro
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5.0 CONCLUSIONS AND POLICY IMPLICAT
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5.5 Access to Market A number of fa
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FAO (2003b). “Women and Food Secu
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Omiti John and Paul Obunde (2002).
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Annex 1: Pearson Correlation Coeffi
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SEXHH SEXLUSER TSECUR VEGCP1 CHILDE
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Part two - Agricultural Markets
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Market Liberalisation and Agricultu
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farms show annual fluctuations, wit
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Figure 2: Recent trends in domestic
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5. The Model The interest of this s
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sources for each sector. α IM ji a
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Savings Households’ savings are a
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The value-added price is defined th
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Specifically, the Government polici
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Table 5: Calculated Tariff Rates (%
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disincentive to farmers. Inability
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competitiveness. The second one is
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Table 7: Wage Rates and Labour Inco
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Similar simulation is undertaken in
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References Block, S. and C.P. Timme
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Tyler, G. J. and Akinboade, O. 1992
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(A.10) ai ∑ P ϖ P i=1,...,3; j =
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(A.32) price (A.33) P Q = P ( 1+ td
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Table A.2: Variables of KEGEM Varia
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VA A i Efficiency parameter in valu
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CHAPTER FIVE Post-Liberalization Ma
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As alluded to earlier, initial agri
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directly to dairy farmers as animal
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to engage in this new role, the gov
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2.0 RESEARCH METHODOLOGY 2.1 Overal
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markets with minor gaps in data ser
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Price-series correlations are conve
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Migori Awendo Postliberalization 1,
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model depends on whether or not the
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Table 6b--Unit root tests for price
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Table 8a--Unit root tests for OLS r
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3.3 The Role of Infrastructure and
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Table 13--Reported distances from t
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Table 15--Reported maize storage pr
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Table 17--Traders’ perception of
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3.3.6.2 Awareness of the Liberaliza
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Retailer (open-air market) 21 13 7
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3.4 Maize Marketing Costs Traders w
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3.4.4 License and Market Fees Accor
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5.Develop farmers’ and traders’
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Coulter, J., and J. A. F. Compton.
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Meilink, A. H. 1987. Food consumpti
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Figure 1 Maize surplus and deficit
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Figure 3 Trends in Maize Prices 199
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Price per 90kg bag (Kshs) Mbeere Di
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Figure 4 Modes of transporting maiz
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Figure 6: Limitations to storage ca
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Figure 8: Problems experienced in a
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CHAPTER SIX Grain Marketing in Addi
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A third, related explanation argues
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educed marketing costs related to p
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1.4. Research questions This study
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1.6. Organization of the report Thi
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the cases, respectively (Table 2.4)
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Brokers believe that most regional
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There is also a close relationship
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Table 2.14: Buyers’ methods for i
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Source: Survey, 2002. Table 2.18: D
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Table 2.22: Method used to grade di
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Table 2.25: Access to credit broker
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It has been reported that grain pur
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3. GRAIN RETAILERS Retailers serve
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Like brokers, retailers use cash or
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Table 3.11: Buyers’ information a
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Table 3.14: Retailers’ views of g
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Getting reliable price information
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Table 4.4: How do you set a sales p
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Table 4.7: Means of settling disput
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a.m. The survey included wholesale
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Table 5.3: Instability index of dai
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Table 5.7: Seasonality index of who
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Figure 5.3: Ratio of wholesale to r
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Table 5.8: Results of stationary te
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Table 5.10: Summary of Granger caus
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holiday sales. The results of the r
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Table 6.1: Storage capacity of the
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Intermarket grain flow is coordinat
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• a legal, regulatory, and enforc
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REFERENCES Al-Hassen, R., A. Dorwar
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Seppala, P. 1998. Decisive liberali
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achieve some welfare objective. The
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Annex Table 2.10: Have you faced di
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Annex Table 2.21: Do you consider p
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Annex Table 3.3: Cost structure of
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Annex Table 4.2: Complementary acti
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CHAPTER SEVEN Post-Harvest Grain Ma
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only (see Abebe 2000: 80-83). That
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of processing as an important post-
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Page 305 and 306: Endowment & access to Resources (e.
Page 307 and 308: Figure 2: The Study Areas (shaded a
Page 309 and 310: (6) β i = β 0 λ i , 0
Page 311 and 312: Intercrop differences Liquidity con
Page 313 and 314: eplace old animals (19 percent of h
Page 315 and 316: Table 5. Number and capacity of gra
Page 317 and 318: Table 7b.Estimated grain loss durin
Page 319 and 320: 7.1.3. Grain Marketing Practices an
Page 321 and 322: 1.8 Producers' price 1.6 1.4 1.2 1
Page 323 and 324: next season, grain prices tend to b
Page 325 and 326: Table 13: Regression results (Tobit
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Page 329 and 330: instruments to mitigate price risks
Page 331 and 332: Coulter, J. and G. Onumah, (2002).
Page 333 and 334: Appendix: Supplementary Tables Appe
Page 335 and 336: CHAPTER EIGHT Collective Action in
Page 337 and 338: The objectives of DRS were to popul
Page 339 and 340: increasing participation. Thus, the
Page 341 and 342: Table 2. Perceived change in benefi
Page 343 and 344: unsatisfactory (Table 8). Flaws in
Page 345 and 346: Table 14. Measures of wealth status
Page 347 and 348: Results from Regression Analysis Ta
Page 349 and 350: However, to maintain these benefits
Page 351 and 352: Table 18. Determinants of participa
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Page 357 and 358: In theory, under PFM, the governmen
Page 359 and 360: 3.2 Desk study The desk study invol
Page 361 and 362: Table 1: Number and gender of indiv
Page 363 and 364: Poverty Increase in number of fishe
Page 365 and 366: Table 5: Responses given by various
Page 367 and 368: wages after the catch is sold (see
Page 369 and 370: 70 60 No of respondents 50 40 30 20
Page 371 and 372: 4.2.3 Lack of attention to social i
Page 373 and 374: 5.3 Regulate the construction of re
Page 375 and 376: REFERENCES Allison, E. H., and P. M
Page 377 and 378: APPENDIXES Appendix A: Districts of
Page 379 and 380: Questions and responses Government
Page 381 and 382: Questions and responses Lack of coo
Page 383 and 384: CHAPTER TEN Animal Health Service D
Page 385 and 386: • Individuals are selected for tr
Page 388 and 389: Makueni district was selected becau
Page 390 and 391: 1.5 Justification of the study The
Page 392 and 393: more sustainable (Leonard 1993; Uma
Page 394 and 395: of defined roles for CBAHWs within
Page 396 and 397: Interviews with veterinary officers
Page 398 and 399: The estimated model was of the form
Page 400 and 401: Gender remains a sensitive issue. P
Page 402 and 403: The most common ailments and diseas
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4.3 Factors influencing the level o
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Table 9 -- Factors influencing the
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Table 10 - Factors determining the
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Table 12 -- Current mean numbers of
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Figure 4: Percentage of household h
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CBAHWs were the most utilized chann
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Users of veterinarians’ services
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Table 18 -- Levels of incomes and l
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higher average calving per cow, whi
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Table 21 -- CBAHWs’ ranking of sp
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epresentative of livestock keepers
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Despite the restriction imposed by
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veterinarians. Such associations co
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References Akabwai, D., V. Shean, a
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Johnson, P. J., and C. Chahuares. 1
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Appendix 1: The Logistic Procedure
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Social Capital and Sustainable Agri
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1.1 Soil conservation programs and
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1.3 Research Objectives and Hypothe
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Institutional and Policy factors -
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land pressure is high (Holden 1991)
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include density of membership in gr
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then summed up according to increas
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Social capital, resource use, and a
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Table 4.4 Farmers’ perception of
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Table 4.5: Empowerment and politica
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Table 4.8: Indicators of collective
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Table 4.10: Comparison of means of
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5. The influence of social capital
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especially when considered on an ad
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households may pay less attention t
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Table 5.3 Determinants of terracing
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and Gichuki 1994). In the 1940s, th
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Table 5.4. Determinants of soil con
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5.3. Social capital, resource use,
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6. Implications for policy and prog
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essential for the formation of exte
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BIBLIOGRPAHY Admassie, Y., L. I. Mw
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Gambetta, D. 1988. Can we trust tru
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Social capital and watershed develo
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Obare, G. A., S. W. Omamo, and J. C
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Washington D.C.: The World Bank Tem
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Appendix: A list of Contributors Ab
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Appendix: Projects Supported Under
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IFPRI Eastern Africa Food Policy Ne
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