The Millennium Ecosystem Assessment and Human Well-Being: Measuring the impacts of surface excavation on Human Well-Being at Dunkwa-On-Offinso in Ghana
As the Millennium Development Goals nears its mark twelvemonth, a batch seems to hold been achieved in many states. However, this has non been without certain challenges. Hitherto, every country’s development docket has been tied to the narrowly defined economic development at the disbursal of the wide base definition of sustainable development. Such an effort in head has so worked to decelerate the gait from which developing states are able to accomplish the eight MDGs as agreed.
Already, there are glowering indicants that all states are non on the same wave-length when it comes to the MDGs accomplishment. The international community has recognized this and has been speedy to suggest post-MDGs dubbed “Sustainable Development Goals ( SDGs )” . Whiles prosecuting this docket, the preposition by the former UN Secretary General Mr. Kofi Annan in 2000 on the protection of the environment and ecosystem, which finally came to be known as the Millennium Ecosystem Assessment in 2001 has further deepened the definition of sustainable development concentrating on the impact of the ecosystem on human wellbeing.
Yet, operationalising this policy model in research particularly quantitatively has been in deficit culminating into a cognition spread.
Without uncertainty, there have been comparatively few surveies quantitatively incorporating the four constituents of the MA policy model to understand the nexus between ES and HWB ( See MA, 2005 ; Nelson et al. , 2009 ; Pereira et al. , 2005 ) . Most quantitative indexs and theoretical accounts of ES have been designed under other conceptual models to run into the demands of other sectors like H2O supply, land usage to reference but a few. More so, before the MA, steps of HWB have been largely developed from the social-psychological, economic, and wellness dimensions with comparatively less accent admiting the ES as driving forces of HWB ( MA, 2005 ; Summers et al. , 2012 ) . Interestingly, some of the indices so discussed in the step of sustainable development such as World Health Organization’s Quality of Life step ( WHOQOL ) , GPI, HPI, HDI among others have been developed and used in related surveies ( Camfield & A ; Skevington, 2008 ; Diener, 1994, 2000, 2009 ; Kahneman & A ; Krueger, 2006 ) . With the coming of the MA, it has progressively been accepted that HWB can non be individually distinguished from the ES ( See Abdallah et al. , 2008 ; Vemuri & A ; Costanza, 2006 ) .
Attempts to this consequence have been made to quantify assorted ES utilizing assorted graduated tables and measure the tradeoffs and synergisms that exist in both natural and unreal ecosystems. The natural capita undertaking ( Kareiva et al. , 2011 ; Nelson et al. , 2009 ) and the economic sciences of ecosystems and Biodiversity ( TEEB ) undertaking ( TEEB, 2010 ) are authoritative illustrations advanced to intensify apprehension of this nexus. Few empirical and theoretical groundss have been discussed in recent surveies detailing out how ES contribute to HWB. For case research workers such as Vemuri and Costanza ( 2006 ) including Abdallah et al. , ( 2008 ) have all contributed in analyzing how different signifiers of capital may be helpful in explicating life satisfaction at the state degree. Yang et al. , ( 2013 ) and Jordan et al. , ( 2010 ) provided a conceptual model to build a composite index of HWB embracing Maslow hierarchy of demands. Yet Summers et al. , ( 2012 ) did a thorough reappraisal on the components of HWB with a focal point on the part to ES. Most of these surveies have been qualitatively done, with merely few following quantitative attack. The cognition spread therefore is on how human use/dependence on ES may impact HWB. In other words, how population or communities have been affected by alterations in ES and the respond thereof. Although theories on environmental alterations are bit by bit emerging with steady advancement, but that of how these alterations affects worlds is non good known ( Dietz et al. , 2009 ) .
The excavation sector in Ghana indisputably contributes vastly to GDP. It is notable that mining’s part to GDP increased from 1.3 % in 1991 to an norm of about 5.2 % between the old ages 2001-2004 ( GMC, 2006 ) . Yet, mining activities in Ghana has led to adverse effects non merely on excavation communities but the economic system at big. An effort to quantify one-year losingss to the economic system through environmental debasement by the Environmental Protection Council in 1988 put conservative estimations at 41.7 billion cedis ( about US $ 19.8 billion ) , the equivalent of 4 % of entire GDP. The impact of mining operations in Ghana both from the big and little graduated table mineworkers are diverse and rather annihilating as it affects HWB. The chief elements of the environment ( i.e. , land, H2O and air ) have been badly affected by mining activities in Ghana. Large piece of lands of land for farming activities have been acquired by mining companies for big scale surface excavation striping mining communities of their beginning of support ( Akabzaa & A ; Darimani, 2001 ) . The proposed survey hence sets to research this, by synergizing the nexus between ES and HWB utilizing MA model when an external driver such as excavation is introduced.
The proposed survey therefore will try to ;
- Develop new index system to mensurate HWB based on the MA model ;
- Demonstrate through empirical observation the application of the index through measuring the impacts of surface excavation on HWB.
Research Design and Methodology
The proposed survey will develop new instrument to mensurate HWB based on the MA model. The development of the study instrument will closely follow Dillman ( 2000 ) and Yang ‘s et al. , ( 2013 ) tailored design attack to maximise possible response rate and at the same clip to guarantee the five dimensions are adequately measured. To this consequence, most inquiries will be formulated as statements on a five-point likert-scale ranging from 1 as “strongly disagree” and 5 as “strongly agree” . The undermentioned stairss will be followed. First, old literature on the list of indexs for each of the five dimensions will be undertaken.
Second, there will be an effort to redefine the steps from the literature to do certain they fit into the MA model and at the same clip add some new steps.
Following measure will be to pre-test the indexs with respondents from outside the proposed research samples and have them revised consequently. The principle for pretesting has been discussed in related surveies.
The proposed survey will so analyze the internal cogency of the points utilizing item-total correlativities to determine if any point is inconsistent with the mean response across all points. This will be in line with the recommendation of Norusis ( 1993 ) , who was of the position that the instrument or measuring must mensurate what it intends to mensurate. Positive terminology for all diction of indexs will used because past literature has indicated that evaluations on negatively worded points are significantly less dependable those positively worded ( Rowe, 2006 ; Rowe & A ; Rowe, 1997 ; Sandoval, 1981 ) .
After the preliminary dependability analysis, the proposed survey will utilize Confirmatory Factor Analysis ( CFA ) to build the overall index and sub-indices. Harmonizing to Yang et Al. ( 2013 ) , CFA addresses several jobs in this type of informations analysis. To get down with, it allows for the drawback of presuming single points are indistinguishable with the underlying theoretical variables ( Eagly & A ; Kulesa, 1997 ) . Second, CFA is a particular signifier of structural equation mold technique that is able to offer the research worker understanding on the proposed theoretical account and the relationship between indexs ( ascertained variables ) and factors ( latent steps ) on one manus and the causal theoretical account associating these steps to each other ( Brown, 2006 ) . CFA is superior to traditional methods ( e.g. chief component analysis ) as it is able to manage cases of multiple indexs for one factor and one index for multiple factors. Furthermore, consequences of CFA provide obliging grounds necessary for concept cogency ( Brown, 2006 ) . CFA allows for hypothesis proving on unequal parts of indexs to the measured factors. CFA besides minimizes the job of non-normal and non-continuous distributions of indexs, and adjusts for measurement mistakes ( Brown, 2006 ; Rowe, 2006 ) .
Expected Consequences and Impacts
The consequences is expected to intensify understanding on the relationship coexisting between ES and human wellbeing, to re-echo the demand for a wide base development that is sustainable as opposed to the narrowly defined economic development. Empirically and theoretically, the quantitative attack is expected to lend to bing literature on this capable country.
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