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Journal of Environment and Earth Science www.iiste.org
ISSN 2224-3216 (Paper) ISSN 2225-0948 (Online)
Vol. 3, No.7, 2013
191
An Assessment of Gender Mix of Manpower in Granite Artisanal
and Small Scale Mining, Southwest Nigeria
M.M. Melodi1*
Z.O. Opafunso2
1. Department of Mining Engineering, Federal University of Technology Akure, Nigeria.
2. Department of Mining Engineering, Federal University of Technology Akure, Nigeria.
*Email of corresponding author: arletmelodi@yahoo.com
Abstract
This study focuses on evaluating granite Artisanal and Small Scale Mining (ASM), women miner contribution,
and the possibility of viable development particularly in Nigeria. A review of literature on global ASM practice,
and issues from the social point of view was carried out to identify the links to the woman miner. Afterwards,
search for granite ASM sites was conducted. Study sites where data were collected were mostly in the South
West and comprised 34 sites. Gender distribution in the entire operation stages was captured for each mine using
nominal binary responses: “n”- none; “y” – yes for either “M” – male or “F” female. These responses were
counted and graphed for the sample population using “COUNTIF” function and chart tool of EXCEL
spreadsheet. Further, from the data, granite ASM condition in the South West of Nigeria were characterized
using graphical and numerical statistical techniques, rating scale development technique,. Results shows in
literature review suggested a high women participation in ASM and highlighted socio-economic issues only. The
next shows the characterization of granite ASM by statistical analysis of raw data, established that the female
gender population is about 80% of manpower, and 15% in entrepreneurial roles. Government should encourage
ASM as a means of poverty alleviation by facilitating credits that can be used to improve ASM conditions and
practice. Especially, as it is seen that ASM is an avenue for many women to be gainfully employed.
Keywords: Mining Operation, gender distribution, gender productivity, granite artisanal and small scale mining,
Nigeria.
1. Introduction
The products of the mining industry have become very essential primary ingredients in almost everything used in
modern times but the human costs component of their production has not been adequately taken into
consideration for proper assessment of the justification of exploitation and patronage. Many mineral driven
economies have the worst indices of human development. The female gender pays the highest price of human
degradation for the extraction and use of minerals and metals. The valuation of the world's minerals does not
take into account these invisible human costs and subsidies especially that women pay. (D'Souza, 2004).
However, the involvement of women in the production of minerals for global consumption is very high,
particularly through ASM. The returns for engaging in ASM for women, besides the general meager wages in
cash, are very low. The costs in terms of social amenities, sexual harassments, labour insecurity, and
inaccessibility to finance, health hazards and marginalization are often not taken into consideration. Therefore,
any study on involvement of Women in ASM is relevant.
Mostly, attention is focused on large companies, but in many parts of the world, particularly in developing
countries, minerals are extracted by ASM, which is carried out by people working with simple tools and
equipment, usually this is an informal sector, outside the legal and regulatory framework. The vast majority of
ASM miners are very poor, exploiting marginal deposits in harsh and often dangerous conditions – and with
considerable impact on the environment. ASM is a livelihood strategy adopted primarily in rural areas. In many
cases, mining represents the most promising, if not the only, income opportunity available. (International Labour
Organization, 1999).
ASM activities will continue for at least as long as poverty persists without alternative means of livelihood. In
addition, the rights of individuals, more so, women, to secure livelihood through ASM must be respected, as
must the objectives of meeting basic needs and maximizing economic wellbeing and financial freedom. It is
therefore essential that efforts be made to maximize the benefits brought by small-scale mining and to avoid or
mitigate the costs. Constraints to achieving this in ASM include poor access to finance and a lack of collective
capacity, particularly for individual or household level Artisanal mining operations. (International Labour
Organization, 1999)
The field study location is within the Southwest basement complex of Nigeria. It is expected that the results
obtained in the case study location can be extended to other parts of the basement complex for the same mineral.
Artisanal mining in Nigeria appears to be a direct consequence of widespread poverty, caused by the decline of
mining industry in Nigeria since the 1970’s; dwindling oil revenue following the eventual fall in the price of
crude oil in international market; and the introduction of Structural Adjustment Programme (SAP) in Nigeria in
Journal of Environment and Earth Science www.iiste.org
ISSN 2224-3216 (Paper) ISSN 2225-0948 (Online)
Vol. 3, No.7, 2013
192
the 1980s. Today ASM dominates the current Nigeria mining sector, and over 90% of mining activities are
illegal.
Nigeria is very rich in economic minerals mineable through ASM. The population is about 150 million, over 40%
of which are women (the highest in Africa). About 50% of the women population reside or obtain their
livelihood in the rural areas. Women participation in ASM can be commonly observed all over Nigeria (visually;
author’s visual survey, personal communication with entrepreneurs and construction minerals suppliers). Taking
analogy of ASM operations in other developed countries of the world and in Africa, it is expedient and necessary
to analyze ASM mining conditions and involvement of women miners in Nigeria with a view to developing
recommendations for improved and increased participation of women for economic development and
standardization of operation. Minerals mined through ASM in Nigeria include: Barites; Limestone; Clay; Granite;
Marble; Quartzite; Silica sand; and Tantalite (Ministry of Solid Minerals Development, MSMD, 2002; MMSD,
1999).
The practice and sustenance of ASM has been observed to depend on significant female-gender participation.
Women miners in ASM are not accorded the benefit and recognition they deserve for their participation in
mineral production in the ASM sector. Moreover, developing countries as Nigeria, rich in ASM minerals, has
not been sufficiently assessed not to mention the contribution of women involvement, possible development and
legalization for job creation, poverty eradication, fashioning of policies for protecting and improving the
participation of the woman-miner; numerical contribution of women miners in ASM production has never been
empirically analyzed..
Government agencies willing to explore ASM for poverty alleviation require empirically based assessments of
the techno-economic characteristics of specific mineral ASM operations, in order to determine effective policies
needed for supporting ASM and female gender involvement.
Solutions to these problems require an assessment and evaluation of ASM operations of specific mineral, women
miner population and impact on production, issues or constraints (technological etc), prospects of development
and viability on investment.
2 Materials and Method
2.1 Study Locations
The main study area is the Southwest basement rock complex of Nigeria. This area is assumed as a cluster of
granite ASM sites of which an exact count is difficult. The ones located were discovered by making enquiries
and speculative searching (scouting). The locations of the sites from which data were obtained are indicated on
the geographical map of the country as shown in Figure 1. The sites are located on the outskirts of towns. Some
sites are shown in Plates 1 and 2
2.2 Gender Distribution in Mining Process
For all the mines, granite mining process was defined. Gender distribution in the entire operation stages was
captured for each mine using nominal binary responses: “n”- none; “y” – yes for either “M” – male or “F”
female. These responses were counted and graphed for the sample population using “COUNTIF” function and
chart tool of EXCEL spreadsheet as shown in Figure 2:
Drilling and blasting operations involve fragmenting large rock mass into sizes (about 50.8 cm) conducive for
crackers. The blaster-men are a special independent group hired when needed by a particular site. They are not
regular workers on a particular site. Heating method of fragmentation is employed in sites with small boulders.
Loading is done by the labourers of marketers who come to buy the products; they are independent as well from
the site management.
2.3 Gender Head Counts of Managers and Crackers in Sample Population
For each site of the sample population, the gender and number of manager/entrepreneur as well as the number of
men and women crackers (Lm, Lw) were recorded. Two coefficients were introduced in the process to reflect the
gender ratio: male coefficient of manpower - Km, and female coefficient of manpower – Kw, per unit. These
data are summarized using graphical and numerical statistical techniques as presented.
3. RESULT AND DISCUSSION
3.1 Mining Operation Stages and Gender Distribution
The counts of binary observations (“y”, “n”) of gender (CBOOG) in the production stages for the sample
population is charted as presented in Figure 2:
Figure 2 shows that drilling and blasting/heating is done only by the male gender; the cracking of rocks to gravel
is carried out by both men and women; measurement, loading is carried out predominantly by men. However,
loading is the responsibility of independent marketers.
Data on entrepreneurial roles and gender distribution, Mgr(m) and Mgr(w), show percentage gender observations
of 85% and 15% respectively (as in Table 1). Currently the involvement of men predominates in this area.
Journal of Environment and Earth Science www.iiste.org
ISSN 2224-3216 (Paper) ISSN 2225-0948 (Online)
Vol. 3, No.7, 2013
193
Women could be encouraged to increase engagement in entrepreneurial roles and not just as hired crackers.
3.2 Gender Coefficients of Manpower
In histograms of Km and Kw presented in Figure 3 and Figure 4, Km ranged from 10-100%, while Kw ranged
from 0-90%; Km is positively skewed, while Kw is negatively skewed. The most frequent range of male-
crackers per site in the sample granite gravel ASM population is quite low – 15% to 20% of manpower, that of
the female gender is higher – 60% to 90% of manpower.
Figure 5 shows that occurrences of manpower (M) vary; M is a variable in ASM. M can vary widely. There are
cases that are as high as 45 to 50 crackers in a site, and can be as low as 5 to 15 crackers. Most sites in the
sample population have between 5 and 10 crackers.
Measures of Central tendencies
Table 1 shows that the mode, median and average of Km are 20%, 34%, and 40% of manpower respectively; and
that for Kw are 80%, 71%, and 66% of manpower respectively.
shows that the mode, median and average of Km are 20%, 34%, and 40% of manpower respectively; and that for
Kw are 80%, 71%, and 66% of manpower respectively.
Measure of Variability
Further, Table 1 shows that coefficient of variation (COV) of Km is 66% and for Kw – 44%. These values show
very high variability of Km and relatively lower variability for Kw.
Measure of Most likely Occurrence
Using the relative frequency approach (as in Figure 6 and Figure 7), the P(Km=20%) and P(Kw=76-90%) are the
highest (18% and 39% respectively). The mode of the modal range for Km is 20%, while that of Kw is 80%.
P(Km) is positively skewed (i.e, skewed to the left); P(Km= 100%) by relative standing is unlikely. P(Kw) is
negatively skewed (i.e, skewed to the right); P(Km<=1%) by relative standing is unlikely.
From the above analysis, it is established that the variability of observations in the sample population is high.
However, some values have significantly high relative occurrences. As a result, and based on the relative
frequency approach, the estimates of Km and Kw can be taken as 20% and 80% of manpower respectively,
which are the respective modes of their modal ranges.
3.3 Gender Gravel production/Cracking rate (Histogram)
The histograms of the gender gravel production rates are presented in Figure 8 and Figure 9. Pm is negatively
skewed, while Pw is positively skewed. The most frequent values for Pm are between 19 to 21 hdp per day. The
most frequent values for Pw are between 9 to 11 hdp per day. Further narrowing of the Bin intervals narrows the
most frequent Pm to approximately 1 tpd and Pw to approximately 0.5 tpd (Figure 10 and Figure 11). The
cracking capacity of men is about twice that of women.
4. CONCLUSION AND RECOMMENDATION
From an analysis of the results, the following conclusions can be made:
1. On mining operation stages and Gender Distribution, results show that drilling and blasting/heating is done
only by the male gender; the cracking of rocks to gravel is carried out by both men and women;
measurement, loading is carried out predominantly by men. It was noted that loading is the responsibility of
independent marketers.
2. On entrepreneurial roles and gender distribution, Mgr(m) and Mgr(w), results show percentage gender
observations of 85% and 15% respectively. Currently the involvement of men predominates in this area.
Locations as Abeokuta have more women at this level than others. Women could be encouraged to increase
engagement in entrepreneurial roles and not just as hired crackers.
3. On Gender coefficients of Manpower (Km and Kw), the most frequent range of male-crackers per site in
granite gravel ASM is quite low – 15% to 20% of manpower, that of the female gender is the highest – 60%
to 90% of manpower. Considering central tendencies, the mode, median and average statistics of Km are
20%, 34%, and 40% of manpower respectively; and that for Kw are 80%, 66%, and 60% of manpower
respectively. Considering Variability, the coefficient of variation (COV) of Km is 66% and for Kw – 44%.
These values show very high variability of Km and relatively lower variability for Kw. On the most likely
occurring values, using the relative frequency approach, the P(Km=20%) and P(Kw=76-90%) are the
highest. The mode for Kw=80%.
4. From the above analysis in (2.), it is established that the variability of observations in the sample population
is high. However, some values have significantly high relative occurrences. As a result, and based on the
relative frequency approach, the estimates of Km and Kw can be taken as 20% and 80% of manpower
respectively. This shows that the involvement of women is very significant and crucial to ASM development.
5. On Gender Gravel production/Cracking rates, the most frequent Pm is 1 tpd and Pw is 0.5 tpd. The cracking
capacity of men is about twice that of women. Considering central tendencies, the mode, median and
average statistics of Pm are 1.0 tpd, 1.0 tpd, and 1.02 tpd respectively; and that for Pw are 0.5 tpd, 0.5 tpd,
Journal of Environment and Earth Science www.iiste.org
ISSN 2224-3216 (Paper) ISSN 2225-0948 (Online)
Vol. 3, No.7, 2013
194
and 0.54 tpd respectively. Considering Variability, that coefficient of variation (COV) statistic of Pm is 20%
and for Pw – 40%. These values show low variability of Pm and Pw. On the most likely occurring values,
using the relative frequency approach, the P(Pm=1.0 tpd) and P(Pw=0.5 tpd) are the highest. In addition, the
central tendency measures for Pm and Pw coincides with the value of highest probability of occurrence.
6. Considering the analysis in (1.) and relative frequency distribution of data, it is established that the
predominating and most likely estimates of Pm and Pw are 1.0 tpd and 0.5 tpd respectively.
From the conclusions made in this study it can be recommended that Government should encourage ASM as a
means of poverty alleviation by facilitating credits that can be used to improve ASM conditions and practice.
Especially, as it is seen that ASM is an avenue for many women to be gainfully employed.
REFERENCES
D'Souza, K. P. (2004). Changing Government and International Perspectives on Artisanal and Small Scale
Mining. Nigeria: FMSMD, 41 pp.
Ministry of Solid Minerals Development, MSMD. (2002). Strategies and blueprint for Sustainable Development
of Artisanal and Small Scale Mining in Nigeria. Abuja: Ministry of Solid Minerals Development, 32 pp.
MMSD. (1999). Nigerian Minerals and Mining Act. In Nigerian Minerals and Mining Act. Nigeria: MMSD.
International Labour Organization. (1999). Social and Labour Issues in Small Scale Mines. Geneva:
International Labour Organization, 93 pp.
Panneerselvam, R. (2009). Research Methodology. NewDelhi-110001: PHI Learning Private Limited, 639 pp.
Keller, G., and Warrack, B. (2003). Statistics for Management and Economics. Pacific Grove, USA: Thompson
Learning Inc, 832 pp.
Figure 1: Geological Map of Nigeria Showing Rock Terrains and Selected Granite ASM Sites
SOUTHWEST
Akure
Ado
Ogotun
Auchi
Abeokuta
Ikere
N
Volcanics
River Niger
Basement complex
Cretaceous
Quaternary (Alluvium)
Tertiary
Granite ASM Site
Locations
120
00’ E40
00’E
120
00’N
40
00’ N
0 100 km
Osogbo
Egbedore
Boripe
Ilesha
Kabba/Bun
u Lokoja
Aja Okuta
Journal of Environment and Earth Science
ISSN 2224-3216 (Paper) ISSN 2225-0948 (Online)
Vol. 3, No.7, 2013
Plate 2: A woman cracking granite rock in a site
Figure 2: Production Stages and Mining and Counts of Binary Observations of Gender
28
0
0
5
10
15
20
25
30
35
40
M F
Drilling & blasting
CBOOG
Women
Granite Boulders
0948 (Online)
195
Plate 1: Blasted area of rock in a site
Plate 2: A woman cracking granite rock in a site
: Production Stages and Mining and Counts of Binary Observations of Gender
Involvement for Sample population
6
0
34 33 34
1
M F M F M F
Heating Cracking Measurement
Production stages
Sledge
Hammer
Stone dusts
Hard core
www.iiste.org
: Production Stages and Mining and Counts of Binary Observations of Gender
33
1
M F
Measurement Loading
Pieces
Journal of Environment and Earth Science www.iiste.org
ISSN 2224-3216 (Paper) ISSN 2225-0948 (Online)
Vol. 3, No.7, 2013
196
Figure 3: Histogram of observed Km
Figure 4: Histogram of observed Kw
Figure 5: Histogram of observed Manpower
4
2
6
1
0
5
3 3
2
0
2
0
1 1 1
0 0 0
3
0%
20%
40%
60%
80%
100%
120%
0
1
2
3
4
5
6
7
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
1
Freq.(Km)
Km, p.u.
Freq.(Km)
Cum.Freq.(Km),%
3
0 0
1 1 1
0
2 2
0
5
2
4
1
5
1
6
0 0
0%
20%
40%
60%
80%
100%
120%
0
1
2
3
4
5
6
7
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
1
Freq.(Kw)
Kw, p.u.
Freq.(Kw)
Cum.Freq.(Kw),%
5
14
4
3
2
1
3
0
1 1
0 0 0
0
5
10
15
5 10 15 20 25 30 35 40 45 50 55 60 More
Frequency(M)
BIN (M)
Frequency(M)
Journal of Environment and Earth Science www.iiste.org
ISSN 2224-3216 (Paper) ISSN 2225-0948 (Online)
Vol. 3, No.7, 2013
197
Table 1: Descriptive Statistics of Lm, Lw, M, Km, Kw and Counts of Mgr(m) and Mgr(w)
DESCRIPT. STAT Mgr(m) Mgr(w) Lm Lw Lm:Lw M Km, p.u. Kw, p.u.
RANGE 1-47 0-20 3-47 0.1-1 0-0.9
MAX 47 20 47 1 0.9
MIN 1 0 3 0.1 0
MODE 1 3 10 0.2 0.80
MEDIAN 3 6.5 10 0.34 0.66
AVERAGE 8 8 1:1 15 0.4 0.60
COUNT (MODE) 8 5 7 5 5
STDEV 10.85 5.61 11.56 0.26 0.26
COV 1.4 0.7 0.8 0.66 0.44
SKEW 1.32 1.03 -1.03
COUNT 29≡ 85% 5≡ 15% 34 34 34
Figure 6: Relative frequencies of Km data
Figure 7: Relative frequencies of Kw data
12%
6%
18%
3%
0%
15%
9% 9%
6%
0%
6%
0%
3% 3% 3%
0% 0% 0%
9%
0%
5%
10%
15%
20%
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
1
Rel.Freq.(Km)
Km, p.u.
Rel.Freq.(Km),%
Median(km)
Average(km)
Mode(km)
9%
0% 0%
3% 3% 3%
0%
6% 6%
0%
15%
6%
12%
3%
15%
3%
18%
0% 0%
0%
5%
10%
15%
20%
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
1
Rel.Freq.(Kw)
Kw, p.u.
Rel.Freq.(Kw),%
Median(Kw)
Average(Kw)
Mode(Kw)
Journal of Environment and Earth Science www.iiste.org
ISSN 2224-3216 (Paper) ISSN 2225-0948 (Online)
Vol. 3, No.7, 2013
198
Figure 8: Histogram of Pm, hdp, in sample population
Figure 9: Histogram of Pw, hdp, in sample population
Figure 10: Frequency and Cumulative Frequency Distribution of Pm Data in tpd.
Figure 11: Frequency and Cumulative Frequency Distribution of Pw Data in tpd.
0
2
4
6
8
10
12
14
16Frequency(Pm)
Pm, hdp
0
2
4
6
8
10
12
14
16
18
Frequency(Pw)
Pw, hdp
0 0 0 0 0 0 0 0 0 0 0 0 0 0
6
1 2 1
14
1 0
2 2 3
0 1 0
0%
50%
100%
150%
0
5
10
15
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
1
1.05
1.1
1.15
1.2
1.25
1.3
1.35
1.4
Freq.(Pm)
Pm, tpd
Freq.(Pm) Cum.Freq.(Pm),%
2
0 0 0 0 0 1 0
16
6
3
1 1 1 1 0 1 0 0 0 1 0 0 0 0 0 0
0%
50%
100%
150%
0
5
10
15
20
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.95
1
1.05
1.1
1.15
1.2
1.25
1.3
1.35
1.4
Freq.(Pw)
Pw, tpd
Freq.(Pw) Cum.Freq.(Pw),%
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An assessment of gender mix of manpower in granite artisanal and small scale mining, southwest nigeria

  • 1. Journal of Environment and Earth Science www.iiste.org ISSN 2224-3216 (Paper) ISSN 2225-0948 (Online) Vol. 3, No.7, 2013 191 An Assessment of Gender Mix of Manpower in Granite Artisanal and Small Scale Mining, Southwest Nigeria M.M. Melodi1* Z.O. Opafunso2 1. Department of Mining Engineering, Federal University of Technology Akure, Nigeria. 2. Department of Mining Engineering, Federal University of Technology Akure, Nigeria. *Email of corresponding author: arletmelodi@yahoo.com Abstract This study focuses on evaluating granite Artisanal and Small Scale Mining (ASM), women miner contribution, and the possibility of viable development particularly in Nigeria. A review of literature on global ASM practice, and issues from the social point of view was carried out to identify the links to the woman miner. Afterwards, search for granite ASM sites was conducted. Study sites where data were collected were mostly in the South West and comprised 34 sites. Gender distribution in the entire operation stages was captured for each mine using nominal binary responses: “n”- none; “y” – yes for either “M” – male or “F” female. These responses were counted and graphed for the sample population using “COUNTIF” function and chart tool of EXCEL spreadsheet. Further, from the data, granite ASM condition in the South West of Nigeria were characterized using graphical and numerical statistical techniques, rating scale development technique,. Results shows in literature review suggested a high women participation in ASM and highlighted socio-economic issues only. The next shows the characterization of granite ASM by statistical analysis of raw data, established that the female gender population is about 80% of manpower, and 15% in entrepreneurial roles. Government should encourage ASM as a means of poverty alleviation by facilitating credits that can be used to improve ASM conditions and practice. Especially, as it is seen that ASM is an avenue for many women to be gainfully employed. Keywords: Mining Operation, gender distribution, gender productivity, granite artisanal and small scale mining, Nigeria. 1. Introduction The products of the mining industry have become very essential primary ingredients in almost everything used in modern times but the human costs component of their production has not been adequately taken into consideration for proper assessment of the justification of exploitation and patronage. Many mineral driven economies have the worst indices of human development. The female gender pays the highest price of human degradation for the extraction and use of minerals and metals. The valuation of the world's minerals does not take into account these invisible human costs and subsidies especially that women pay. (D'Souza, 2004). However, the involvement of women in the production of minerals for global consumption is very high, particularly through ASM. The returns for engaging in ASM for women, besides the general meager wages in cash, are very low. The costs in terms of social amenities, sexual harassments, labour insecurity, and inaccessibility to finance, health hazards and marginalization are often not taken into consideration. Therefore, any study on involvement of Women in ASM is relevant. Mostly, attention is focused on large companies, but in many parts of the world, particularly in developing countries, minerals are extracted by ASM, which is carried out by people working with simple tools and equipment, usually this is an informal sector, outside the legal and regulatory framework. The vast majority of ASM miners are very poor, exploiting marginal deposits in harsh and often dangerous conditions – and with considerable impact on the environment. ASM is a livelihood strategy adopted primarily in rural areas. In many cases, mining represents the most promising, if not the only, income opportunity available. (International Labour Organization, 1999). ASM activities will continue for at least as long as poverty persists without alternative means of livelihood. In addition, the rights of individuals, more so, women, to secure livelihood through ASM must be respected, as must the objectives of meeting basic needs and maximizing economic wellbeing and financial freedom. It is therefore essential that efforts be made to maximize the benefits brought by small-scale mining and to avoid or mitigate the costs. Constraints to achieving this in ASM include poor access to finance and a lack of collective capacity, particularly for individual or household level Artisanal mining operations. (International Labour Organization, 1999) The field study location is within the Southwest basement complex of Nigeria. It is expected that the results obtained in the case study location can be extended to other parts of the basement complex for the same mineral. Artisanal mining in Nigeria appears to be a direct consequence of widespread poverty, caused by the decline of mining industry in Nigeria since the 1970’s; dwindling oil revenue following the eventual fall in the price of crude oil in international market; and the introduction of Structural Adjustment Programme (SAP) in Nigeria in
  • 2. Journal of Environment and Earth Science www.iiste.org ISSN 2224-3216 (Paper) ISSN 2225-0948 (Online) Vol. 3, No.7, 2013 192 the 1980s. Today ASM dominates the current Nigeria mining sector, and over 90% of mining activities are illegal. Nigeria is very rich in economic minerals mineable through ASM. The population is about 150 million, over 40% of which are women (the highest in Africa). About 50% of the women population reside or obtain their livelihood in the rural areas. Women participation in ASM can be commonly observed all over Nigeria (visually; author’s visual survey, personal communication with entrepreneurs and construction minerals suppliers). Taking analogy of ASM operations in other developed countries of the world and in Africa, it is expedient and necessary to analyze ASM mining conditions and involvement of women miners in Nigeria with a view to developing recommendations for improved and increased participation of women for economic development and standardization of operation. Minerals mined through ASM in Nigeria include: Barites; Limestone; Clay; Granite; Marble; Quartzite; Silica sand; and Tantalite (Ministry of Solid Minerals Development, MSMD, 2002; MMSD, 1999). The practice and sustenance of ASM has been observed to depend on significant female-gender participation. Women miners in ASM are not accorded the benefit and recognition they deserve for their participation in mineral production in the ASM sector. Moreover, developing countries as Nigeria, rich in ASM minerals, has not been sufficiently assessed not to mention the contribution of women involvement, possible development and legalization for job creation, poverty eradication, fashioning of policies for protecting and improving the participation of the woman-miner; numerical contribution of women miners in ASM production has never been empirically analyzed.. Government agencies willing to explore ASM for poverty alleviation require empirically based assessments of the techno-economic characteristics of specific mineral ASM operations, in order to determine effective policies needed for supporting ASM and female gender involvement. Solutions to these problems require an assessment and evaluation of ASM operations of specific mineral, women miner population and impact on production, issues or constraints (technological etc), prospects of development and viability on investment. 2 Materials and Method 2.1 Study Locations The main study area is the Southwest basement rock complex of Nigeria. This area is assumed as a cluster of granite ASM sites of which an exact count is difficult. The ones located were discovered by making enquiries and speculative searching (scouting). The locations of the sites from which data were obtained are indicated on the geographical map of the country as shown in Figure 1. The sites are located on the outskirts of towns. Some sites are shown in Plates 1 and 2 2.2 Gender Distribution in Mining Process For all the mines, granite mining process was defined. Gender distribution in the entire operation stages was captured for each mine using nominal binary responses: “n”- none; “y” – yes for either “M” – male or “F” female. These responses were counted and graphed for the sample population using “COUNTIF” function and chart tool of EXCEL spreadsheet as shown in Figure 2: Drilling and blasting operations involve fragmenting large rock mass into sizes (about 50.8 cm) conducive for crackers. The blaster-men are a special independent group hired when needed by a particular site. They are not regular workers on a particular site. Heating method of fragmentation is employed in sites with small boulders. Loading is done by the labourers of marketers who come to buy the products; they are independent as well from the site management. 2.3 Gender Head Counts of Managers and Crackers in Sample Population For each site of the sample population, the gender and number of manager/entrepreneur as well as the number of men and women crackers (Lm, Lw) were recorded. Two coefficients were introduced in the process to reflect the gender ratio: male coefficient of manpower - Km, and female coefficient of manpower – Kw, per unit. These data are summarized using graphical and numerical statistical techniques as presented. 3. RESULT AND DISCUSSION 3.1 Mining Operation Stages and Gender Distribution The counts of binary observations (“y”, “n”) of gender (CBOOG) in the production stages for the sample population is charted as presented in Figure 2: Figure 2 shows that drilling and blasting/heating is done only by the male gender; the cracking of rocks to gravel is carried out by both men and women; measurement, loading is carried out predominantly by men. However, loading is the responsibility of independent marketers. Data on entrepreneurial roles and gender distribution, Mgr(m) and Mgr(w), show percentage gender observations of 85% and 15% respectively (as in Table 1). Currently the involvement of men predominates in this area.
  • 3. Journal of Environment and Earth Science www.iiste.org ISSN 2224-3216 (Paper) ISSN 2225-0948 (Online) Vol. 3, No.7, 2013 193 Women could be encouraged to increase engagement in entrepreneurial roles and not just as hired crackers. 3.2 Gender Coefficients of Manpower In histograms of Km and Kw presented in Figure 3 and Figure 4, Km ranged from 10-100%, while Kw ranged from 0-90%; Km is positively skewed, while Kw is negatively skewed. The most frequent range of male- crackers per site in the sample granite gravel ASM population is quite low – 15% to 20% of manpower, that of the female gender is higher – 60% to 90% of manpower. Figure 5 shows that occurrences of manpower (M) vary; M is a variable in ASM. M can vary widely. There are cases that are as high as 45 to 50 crackers in a site, and can be as low as 5 to 15 crackers. Most sites in the sample population have between 5 and 10 crackers. Measures of Central tendencies Table 1 shows that the mode, median and average of Km are 20%, 34%, and 40% of manpower respectively; and that for Kw are 80%, 71%, and 66% of manpower respectively. shows that the mode, median and average of Km are 20%, 34%, and 40% of manpower respectively; and that for Kw are 80%, 71%, and 66% of manpower respectively. Measure of Variability Further, Table 1 shows that coefficient of variation (COV) of Km is 66% and for Kw – 44%. These values show very high variability of Km and relatively lower variability for Kw. Measure of Most likely Occurrence Using the relative frequency approach (as in Figure 6 and Figure 7), the P(Km=20%) and P(Kw=76-90%) are the highest (18% and 39% respectively). The mode of the modal range for Km is 20%, while that of Kw is 80%. P(Km) is positively skewed (i.e, skewed to the left); P(Km= 100%) by relative standing is unlikely. P(Kw) is negatively skewed (i.e, skewed to the right); P(Km<=1%) by relative standing is unlikely. From the above analysis, it is established that the variability of observations in the sample population is high. However, some values have significantly high relative occurrences. As a result, and based on the relative frequency approach, the estimates of Km and Kw can be taken as 20% and 80% of manpower respectively, which are the respective modes of their modal ranges. 3.3 Gender Gravel production/Cracking rate (Histogram) The histograms of the gender gravel production rates are presented in Figure 8 and Figure 9. Pm is negatively skewed, while Pw is positively skewed. The most frequent values for Pm are between 19 to 21 hdp per day. The most frequent values for Pw are between 9 to 11 hdp per day. Further narrowing of the Bin intervals narrows the most frequent Pm to approximately 1 tpd and Pw to approximately 0.5 tpd (Figure 10 and Figure 11). The cracking capacity of men is about twice that of women. 4. CONCLUSION AND RECOMMENDATION From an analysis of the results, the following conclusions can be made: 1. On mining operation stages and Gender Distribution, results show that drilling and blasting/heating is done only by the male gender; the cracking of rocks to gravel is carried out by both men and women; measurement, loading is carried out predominantly by men. It was noted that loading is the responsibility of independent marketers. 2. On entrepreneurial roles and gender distribution, Mgr(m) and Mgr(w), results show percentage gender observations of 85% and 15% respectively. Currently the involvement of men predominates in this area. Locations as Abeokuta have more women at this level than others. Women could be encouraged to increase engagement in entrepreneurial roles and not just as hired crackers. 3. On Gender coefficients of Manpower (Km and Kw), the most frequent range of male-crackers per site in granite gravel ASM is quite low – 15% to 20% of manpower, that of the female gender is the highest – 60% to 90% of manpower. Considering central tendencies, the mode, median and average statistics of Km are 20%, 34%, and 40% of manpower respectively; and that for Kw are 80%, 66%, and 60% of manpower respectively. Considering Variability, the coefficient of variation (COV) of Km is 66% and for Kw – 44%. These values show very high variability of Km and relatively lower variability for Kw. On the most likely occurring values, using the relative frequency approach, the P(Km=20%) and P(Kw=76-90%) are the highest. The mode for Kw=80%. 4. From the above analysis in (2.), it is established that the variability of observations in the sample population is high. However, some values have significantly high relative occurrences. As a result, and based on the relative frequency approach, the estimates of Km and Kw can be taken as 20% and 80% of manpower respectively. This shows that the involvement of women is very significant and crucial to ASM development. 5. On Gender Gravel production/Cracking rates, the most frequent Pm is 1 tpd and Pw is 0.5 tpd. The cracking capacity of men is about twice that of women. Considering central tendencies, the mode, median and average statistics of Pm are 1.0 tpd, 1.0 tpd, and 1.02 tpd respectively; and that for Pw are 0.5 tpd, 0.5 tpd,
  • 4. Journal of Environment and Earth Science www.iiste.org ISSN 2224-3216 (Paper) ISSN 2225-0948 (Online) Vol. 3, No.7, 2013 194 and 0.54 tpd respectively. Considering Variability, that coefficient of variation (COV) statistic of Pm is 20% and for Pw – 40%. These values show low variability of Pm and Pw. On the most likely occurring values, using the relative frequency approach, the P(Pm=1.0 tpd) and P(Pw=0.5 tpd) are the highest. In addition, the central tendency measures for Pm and Pw coincides with the value of highest probability of occurrence. 6. Considering the analysis in (1.) and relative frequency distribution of data, it is established that the predominating and most likely estimates of Pm and Pw are 1.0 tpd and 0.5 tpd respectively. From the conclusions made in this study it can be recommended that Government should encourage ASM as a means of poverty alleviation by facilitating credits that can be used to improve ASM conditions and practice. Especially, as it is seen that ASM is an avenue for many women to be gainfully employed. REFERENCES D'Souza, K. P. (2004). Changing Government and International Perspectives on Artisanal and Small Scale Mining. Nigeria: FMSMD, 41 pp. Ministry of Solid Minerals Development, MSMD. (2002). Strategies and blueprint for Sustainable Development of Artisanal and Small Scale Mining in Nigeria. Abuja: Ministry of Solid Minerals Development, 32 pp. MMSD. (1999). Nigerian Minerals and Mining Act. In Nigerian Minerals and Mining Act. Nigeria: MMSD. International Labour Organization. (1999). Social and Labour Issues in Small Scale Mines. Geneva: International Labour Organization, 93 pp. Panneerselvam, R. (2009). Research Methodology. NewDelhi-110001: PHI Learning Private Limited, 639 pp. Keller, G., and Warrack, B. (2003). Statistics for Management and Economics. Pacific Grove, USA: Thompson Learning Inc, 832 pp. Figure 1: Geological Map of Nigeria Showing Rock Terrains and Selected Granite ASM Sites SOUTHWEST Akure Ado Ogotun Auchi Abeokuta Ikere N Volcanics River Niger Basement complex Cretaceous Quaternary (Alluvium) Tertiary Granite ASM Site Locations 120 00’ E40 00’E 120 00’N 40 00’ N 0 100 km Osogbo Egbedore Boripe Ilesha Kabba/Bun u Lokoja Aja Okuta
  • 5. Journal of Environment and Earth Science ISSN 2224-3216 (Paper) ISSN 2225-0948 (Online) Vol. 3, No.7, 2013 Plate 2: A woman cracking granite rock in a site Figure 2: Production Stages and Mining and Counts of Binary Observations of Gender 28 0 0 5 10 15 20 25 30 35 40 M F Drilling & blasting CBOOG Women Granite Boulders 0948 (Online) 195 Plate 1: Blasted area of rock in a site Plate 2: A woman cracking granite rock in a site : Production Stages and Mining and Counts of Binary Observations of Gender Involvement for Sample population 6 0 34 33 34 1 M F M F M F Heating Cracking Measurement Production stages Sledge Hammer Stone dusts Hard core www.iiste.org : Production Stages and Mining and Counts of Binary Observations of Gender 33 1 M F Measurement Loading Pieces
  • 6. Journal of Environment and Earth Science www.iiste.org ISSN 2224-3216 (Paper) ISSN 2225-0948 (Online) Vol. 3, No.7, 2013 196 Figure 3: Histogram of observed Km Figure 4: Histogram of observed Kw Figure 5: Histogram of observed Manpower 4 2 6 1 0 5 3 3 2 0 2 0 1 1 1 0 0 0 3 0% 20% 40% 60% 80% 100% 120% 0 1 2 3 4 5 6 7 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1 Freq.(Km) Km, p.u. Freq.(Km) Cum.Freq.(Km),% 3 0 0 1 1 1 0 2 2 0 5 2 4 1 5 1 6 0 0 0% 20% 40% 60% 80% 100% 120% 0 1 2 3 4 5 6 7 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1 Freq.(Kw) Kw, p.u. Freq.(Kw) Cum.Freq.(Kw),% 5 14 4 3 2 1 3 0 1 1 0 0 0 0 5 10 15 5 10 15 20 25 30 35 40 45 50 55 60 More Frequency(M) BIN (M) Frequency(M)
  • 7. Journal of Environment and Earth Science www.iiste.org ISSN 2224-3216 (Paper) ISSN 2225-0948 (Online) Vol. 3, No.7, 2013 197 Table 1: Descriptive Statistics of Lm, Lw, M, Km, Kw and Counts of Mgr(m) and Mgr(w) DESCRIPT. STAT Mgr(m) Mgr(w) Lm Lw Lm:Lw M Km, p.u. Kw, p.u. RANGE 1-47 0-20 3-47 0.1-1 0-0.9 MAX 47 20 47 1 0.9 MIN 1 0 3 0.1 0 MODE 1 3 10 0.2 0.80 MEDIAN 3 6.5 10 0.34 0.66 AVERAGE 8 8 1:1 15 0.4 0.60 COUNT (MODE) 8 5 7 5 5 STDEV 10.85 5.61 11.56 0.26 0.26 COV 1.4 0.7 0.8 0.66 0.44 SKEW 1.32 1.03 -1.03 COUNT 29≡ 85% 5≡ 15% 34 34 34 Figure 6: Relative frequencies of Km data Figure 7: Relative frequencies of Kw data 12% 6% 18% 3% 0% 15% 9% 9% 6% 0% 6% 0% 3% 3% 3% 0% 0% 0% 9% 0% 5% 10% 15% 20% 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1 Rel.Freq.(Km) Km, p.u. Rel.Freq.(Km),% Median(km) Average(km) Mode(km) 9% 0% 0% 3% 3% 3% 0% 6% 6% 0% 15% 6% 12% 3% 15% 3% 18% 0% 0% 0% 5% 10% 15% 20% 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1 Rel.Freq.(Kw) Kw, p.u. Rel.Freq.(Kw),% Median(Kw) Average(Kw) Mode(Kw)
  • 8. Journal of Environment and Earth Science www.iiste.org ISSN 2224-3216 (Paper) ISSN 2225-0948 (Online) Vol. 3, No.7, 2013 198 Figure 8: Histogram of Pm, hdp, in sample population Figure 9: Histogram of Pw, hdp, in sample population Figure 10: Frequency and Cumulative Frequency Distribution of Pm Data in tpd. Figure 11: Frequency and Cumulative Frequency Distribution of Pw Data in tpd. 0 2 4 6 8 10 12 14 16Frequency(Pm) Pm, hdp 0 2 4 6 8 10 12 14 16 18 Frequency(Pw) Pw, hdp 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 1 2 1 14 1 0 2 2 3 0 1 0 0% 50% 100% 150% 0 5 10 15 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4 Freq.(Pm) Pm, tpd Freq.(Pm) Cum.Freq.(Pm),% 2 0 0 0 0 0 1 0 16 6 3 1 1 1 1 0 1 0 0 0 1 0 0 0 0 0 0 0% 50% 100% 150% 0 5 10 15 20 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4 Freq.(Pw) Pw, tpd Freq.(Pw) Cum.Freq.(Pw),%
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