Waste picking and livelihoods in Grahamstown, South Africa. Trash or
treasure?
Dale Earle, Nic Andrew, Michelle Nott, Michaella Lampe, Amy-lee Greeves, Relebohile
Chabeli, Awongiwe Mabutyana
Environmental Science 3 2014
Rhodes University
Supervisor: Gladman Thondhlana
1
Contents
1.
Introduction ........................................................................................................................ 5
2.
The case study town, Grahamstown ................................................................................... 7
3.
Methods .............................................................................................................................. 8
3.1 Data collection ................................................................................................................. 8
3.2 Data analysis ................................................................................................................. 10
4.
Results and discussion ...................................................................................................... 11
4.1 Socio-economic characteristics of the respondents and households ............................. 11
4.2 Waste collection and contribution to household income ............................................... 11
4.3 Key sources of waste picking income (all types of all material collected) .................... 13
4.5 Determinants of waste picking income .......................................................................... 15
4.6 Waste pickers’ perceptions on challenges encountered ................................................ 17
5.
Recommendations and conclusion ................................................................................... 17
References ................................................................................................................................ 18
2
List of figures
Figure 1: Map of Grahamstown……………………………………………………………. .8
Figure 2: Average difference in Total Annual Income with and without Waste Picking
Income
………………………………………………………………………………………Err
or! Bookmark not defined.2
Figure 3: Recyclable materials collected and sold by waste pickers……………………….
Error! Bookmark not defined.3
List of tables
Table 1: Poverty incidence and poverty gap with and without waste picking income…….145
Table 2: Multiple linear regression
analysis……………………………………………….Error! Bookmark not defined.6
3
Abstract
This study examines the contribution of waste picking to the livelihoods of waste pickers in a
medium sized-town of Grahamstown, South Africa. We collected data through a structured
survey of 60 waste pickers and their households. Most households are poor, living on less than
UDS1 a day. Waste picking contributes about 70 % of total household income. An analysis of
household income with and without waste picking income using the food poverty line showed
that waste picking reduced poverty incidence and poverty gap by 29 % and 68 % respectively.
Household size, gender, frequency of waste collection, access to transport and poverty status
were the major determinants of waste picking income. The findings highlight the importance
of waste picking income to the livelihoods of the urban poor, and the need to acknowledge and
support waste picking as a potential poverty alleviation strategy in medium sized towns of
South Africa, where job opportunities are often limited.
Key words: Waste picking, livelihoods, urban poor, poverty
4
1. Introduction
Globally, the contribution of waste picking on the livelihoods of waste pickers’ is being
increasingly explored, particularly in developing countries. Empirical evidence increasingly
shows that waste picking is a key source of livelihood improvement for many poor urban
dwellers (Njoroge et al., 2013). In India for example, studies have found that many women,
often positioned in the lower echelons of poverty, have no choice but collect waste as an income
generating activity (Huysman, 1994). According to Huysman (1994), there are limited
opportunities for such women in the labour market due to their economic and social status and
are therefore forced to take on informal and underestimated jobs such as waste picking. In
Duoala, Cameroon, waste picking has been shown to reduce poverty among the poor waste
pickers (Mbeng, 2013). In a study of waste picking in the United States, Mamphitha (2011),
found that the mean monthly income of a waste picker was $41.28 (± R454.08). Often waste
pickers choose what they collect in terms of what they can sell and use the most (Schneck and
Blaauw, 2011). Waste pickers are the initial link in the recycling sequence and form the base
in the hierarchy of waste management (Nzeadibe et al., 2012). It is also argued that waste
collection activities while providing an income to the urban poor, indirectly contributes to
recycling in cities. A South African recycling company, PETCO, reported that 23,000 tonnes
of PET such as milk bottles were collected in 2008 (Mamphitha, 2011) contributing to
mitigating the effects of climate change by reducing greenhouse gas emissions through the
recycling of waste (SEWA, 2009).
Despite the potential benefits of waste picking to the urban poor and overburdened waste
management services, waste pickers’ are faced with various challenges ranging from social
exclusion, health risks and well-being to unfair market prices. For example, there are some
negative connotations attached to waste pickers as waste picking is often conceived to be a
symbol of poverty (Medina, 2007). It is also not uncommon to find waste pickers working
without proper protective equipment – which endangers their health and well-being. Nzeadibe
et al. (2012) revealed that 81.5% of waste pickers were confident that the health-related
challenges they faced were not associated with their job. With regards to unfair market prices,
5
waste picking forms part of a complex waste hierarchy and waste pickers’ usually lie at the
bottom of that hierarchy, while merchants or recycling companies disproportionately benefit
from the exchange money or goods for recyclable materials brought in by waste pickers’. Often
what waste pickers’ get paid is largely determined by the merchant and some merchants exploit
waste pickers’ by paying them the bare minimum for waste materials (Schenck and Blaauw,
2011). Further, different waste types also fetch various returns and therefore waste pickers
often experienced fluctuations regarding their income (Mamphitha, 2011). According to
Sapuay (n.d.) lack of safety, adverse working conditions and low incomes are indicative of the
fact that waste pickers are often poor and desperate urban dwellers who collect waste for basic
survival. Due to poor recognition of the waste income sector, waste picking is often ignored
and very little effort is made to support waste picking activities (Wilson et al., 2006).
As urban populations continue to grow faster, the majority of urban migrants are moving to
smaller and medium sized towns of less than 500 000 inhabitants (UN HABITAT, 2006; World
Bank, 2009), as they seek employment opportunities (Montgomery, 2008). The effects of
urbanisation are more immediate and noticeable in relatively small and medium sized towns
(Drakakis-Smith, 1995). However, most studies on the contribution of waste picking have been
done in large cities (e.g. New Delhi and Bangalore in India, Durban in South Africa). In South
Africa, medium sized towns have seen the influx of people from nearby rural areas as rural
dwellers seek for employment opportunities. Thus, waste picking can be seen as a potential
source of livelihood especially as unemployment levels remain very high. However, despite
the continued recognition of waste picking to the livelihoods of the urban poor world-wide,
there is a still limited empirical evidence on the value of waste picking and the challenges faced
by waste pickers’ in South African medium-sized towns. Further, while a lot has been written
on the contribution of waste picking to the urban poor, comparatively few studies have explored
the waste picking-poverty links. Omission of income from waste picking in urban-based
poverty assessments may result in underestimation of the urban poor’s income, non-recognition
of the waste picking sector and subsequently, adoption of poorly informed poverty alleviation
and waste management interventions.
Therefore, to get the ‘bigger picture’ on waste picking and livelihoods, there is a need for
studies in medium-sized towns and examining waste picking and its influence on poverty
reduction. Empirical evidence could be used to better inform various waste management
6
options and leverage some responsiveness from interested stakeholders such as government
and NGOs on the plight of waste pickers’ and acknowledgement of waste picking as a cost
effective way for managing waste. In light of this background, this research has four main
objectives. First, the paper aims to enhance understanding on the contribution of waste picking
to the livelihoods of waste pickers’ and impact on poverty alleviation using a medium smallsized South African town as a case study. Second, the study explores the socio-economic
factors that influence waste picking income. Third, we document waste pickers’ perspectives
on the challenges they face in waste picking activities. Fourth, we discuss the implications of
the findings on waste picking debates and on a more practical level, what this means for waste
management practices in Makana Municipality. We hypothesise that waste picking is a
significant contributor to the urban poor’s livelihoods.
2. The case study town, Grahamstown
Grahamstown is a medium-sized town located in the Eastern Cape Province of South Africa
(33◦ 31’ S, 26◦ 53’). The temperature in Grahamstown ranges from -4°C to 42°C and the mean
annual precipitation is 550 mm (Etengeneng, 2012). The town is administered by the Makana
Municipality. Grahamstown, similar to other South African towns, has a sizeable proportion of
poor urban people as evidenced by a high dependence on government social grants. The
settlements in Grahamstown consist of 27 built-up residential areas and Rhodes University
(Etengeneng, 2012). According to Davenport et al. (2012) the township is home to 9120
households which accommodate the majority of the people living in Grahamstown. Based on
an estimate from 2003, the population was greater than 124 000 (Etengeneng, 2012) and
continues to escalate (Davenport et al., 2012; Adama, 2014). The major formal employers in
Grahamstown are the military, primary and high schools, Rhodes University and other service
related industries such as retail shops and financial institutions. Most people are also employed
in the informal sector including hairdressing, housekeeping and street vendoring among others.
7
Figure 1: Location of Grahamstown
Like many authorities in developing countries’, cities and towns (Montgomery, 2008), the local
Makana Municipality of Grahamstown face many service delivery challenges primarily due to
growing urban populations. Some of these challenges include providing work opportunities to
the growing number of urban poor who often have lower education levels to get into
mainstream formal jobs (Gwedla and Shackleton, 2014) and waste management given high
production of waste (Montgomery, 2008).
3. Methods
3.1 Data collection
Data was collected between April and July 2014 using structured questionnaires with open and
closed ended questions. The questionnaire was designed to capture socio-demographic
information and all the income sources of the respondents and their households. The section
on waste picking activities collected information on all the different types of material that was
collected, frequency of collection, what they actually did with the collected material, how
collected materials were transported, the reported incomes generated from commercialisation,
circumstances leading to waste picking activities and waste pickers’ perspectives on the
challenges they faced.
8
We attempted to approach all waste pickers at the main Grahamstown waste dump and along
the streets for the surveys. A total of 60 waste pickers participated in the surveys – with a fair
presentation of dump and street waste pickers. We stopped the surveys when we realised we
were encountering previously interviewed respondents. We collected data after informing the
participants about the intention and purposes of the study. We also highlighted that
participation was completely voluntary though some respondents asked for incentives. Further,
we made assurances of participants’ anonymity and confidentiality of their responses. This
study considers waste as discarded materials which are of no use any more to the previous
owner and, waste pickers’ as individuals who collect discarded materials from streets, outside
houses and/or businesses for income and survival, following Pongrácz and Pohjola (2004).
9
3.2 Data analysis
We generated income accounts to estimate the contribution of waste picking income to the
respondents’ household income portfolios. We estimated waste income as reported income per
day x frequency of collection per week x 52 weeks per week. In our calculation of waste picking
income, the opportunity costs of labour were not considered because according to Gram (2001),
deducting these in situations of low earning skills and negligible labour opportunities can be
misleading. All the reported waste income values in this study were estimated at a gross income
basis. During the data collection period, the average exchange rate between the South African
Rand (ZAR) and the U.S. Dollar was roughly U.S. $1.00 = ZAR10.5.
We used a headcount index and poverty gap index to measure the proportion of poor
households (poverty incidence) and the depth of poverty with and without waste picking
income respectively. The poverty gap index measures the extent to which households or
individuals on average fall below the poverty line, and expresses it as a percentage of the
poverty line. We calculated the poverty gap index as the poverty gap (Gi) [poverty line (z) less
average actual income (yi) for individuals], expressed as a percentage of the poverty line (z).
According to Leibbrandt et al. (2010), the poverty gap index puts more emphasis on the poorest
of the poor. We used both household income and per capita income as the income measure, for
easy comparisons across the datasets available. While there is a plethora of poverty measures
in the poverty literature, we used a 2011 food poverty line of ZAR3 852 (US$367) per capita
per year (or ZAR321 (US$31) per month) (Statistics South Africa, 2014). Our choice of the
food poverty line is based on the fact that one of the many challenges facing the urban poor is
food insecurity (UN- HABITAT, 2006).
We used a simple multiple regression analysis to estimate the effect of various socio-economic
factors on waste picking income. The choice of our explanatory variables (standard income,
age, gender and education of respondent, frequency of collection, poverty status, and method
of waste transportation) were based on economic theory and common sense. For example, we
hypothesised that as income from other sources increases, dependence on waste picking income
would decrease since households will have other buffers to fall on in times of shocks. With
regards to age, we expected that as age increased, waste income was likely to decline as energy
levels to collect declines with aging. We expected a positive relationship between access to
10
transport (e.g. cars) and waste income because access to transport can increase the amount of
waste collected. A high frequency of waste picking was obviously expected to result in more
waste income. Further, given that most of the respondents lived below the poverty line, we
used a poverty status dummy to determine its influence on waste picking income.
4. Results and discussion
4.1 Socio-economic characteristics of the respondents and households
Out of all the respondents surveyed 78 % were males. The average age of all the respondents
was 39 (±16.46) years. The 20-29 years age group was the dominant one, constituting 34 %
of all the respondents. The average years spent at school were 6.5 (±3.59). Out of all the
respondents, 66 % did not have a secondary education – perhaps explaining why most
respondents (97 %) did not have jobs. Moreover, Nzeadibe et al. (2012) found that 77 % of
waste pickers would prefer to complete formal education and thus be able to promote
livelihood security in their households. If waste pickers have a higher level of education, they
may possess skills that could contribute to the betterment of their livelihoods. Most of the
respondents (80 %) were single while the remaining were either married or widowed. The
average household size was 4 (±2.11) people. Thirty five percent of the respondents received
social grants – suggestive of the fact that most of the households are poor (Shackleton et al.,
2008).
4.2 Waste collection and contribution to household income
On average respondents collected waste 4 (±1.71) days a week ranging from 1-7 days and spent
an average of 7 (±3) hours per day ranging from 2-11 hours. Sixty percent of the respondents
carried the waste on their heads or backs to the recycling companies whereas the remaining
respondents either walked or got lifts to the recycling companies. Most households (61 %) were
generally poor living on less than USD1 per day. Waste picking income contributed about 70
% (ZAR 8365.28 or USD 797) of the total annual income per household while the remaining
proportion was mainly from government grants.
Figure 2 shows the average total household annual incomes with and without waste picking
income. The mean total annual income was approximately ZAR13161 (USD1253) and
ZAR4796 (USD474) with and without waste picking income respectively. There was a
significant difference between total annual income with and without waste picking (t = 3.849;
11
p =0.000). This indicates that waste picking is a substantial contributor to the livelihoods of
the urban poor (Langenhoven and Dyssel, 2007).
R 4,500.00
R 4,000.00
R 3,851.51
Average annual income (ZAR)
R 3,500.00
R 3,000.00
R 2,500.00
R 2,000.00
R 1,500.00
R 1,215.48
R 1,000.00
R 500.00
R 0.00
With waste picking income
Without waste picking income
Average annual income per capita
Figure 2: Mean household annual income with and without waste picking income per capita
The findings demonstrate that waste picking is a key livelihood source for the urban poor
consistent with findings elsewhere. For example, figure 2 shows that the majority of household
income is derived from waste picking (t = 4.883; p = 0.000). In a study on waste picking as a
survival strategy for Indian woman, Huysman (1994) found that woman mostly worked in this
informal sector for the financial benefits. Waste collection within communities around the
world has proved to be a great contribution to the livelihoods of low income communities
(Njoroge et al., 2013). According to Wilson et al. (2006), in developing countries, waste
picking is often carried out by the poor and marginalised social groups as a source of income
and daily survival. Similarly, Nkosi and Muzenda (2013) argue that poverty is the main driver
of waste picking in South Africa.
12
4.3 Key sources of waste picking income (all types of all material collected)
The reported key sources of waste were plastic, glass, metal, paper, rubber and cardboard. As
shown in Figure 3, the most commonly collected and sold material were plastic, glass and metal
cited by (52%), (43%) and (38%) of the respondents respectively. Paper, cardboard and rubber
were collected the least cited by 18%, 10% and 5%. Each of the waste material was
predominantly collected for sale but was also the respondents mentioned using at least on
material for household purposes.
60.0
51.7
Proportion (%) of respondents
50.0
43.3
38.3
40.0
30.0
18.3
20.0
10.0
10.0
5.0
0.0
Plastic
Glass
Paper
Metal
Cardboard
Rubber
Type of waste collected
Figure 3: The main recyclable materials collected and sold by waste pickers
Waste pickers’ preference of certain waste was dependent on what they could sell or use at
home consistent with other studies (Schenck and Blaauw, 2011). In this study, waste pickers
reported that plastic, glass and metal were waste materials mostly sought after by merchants.
These materials were sometimes used at home for domestic purposes – for example empty
plastic buckets and bottles are used for water collection and storage and metal as building
material. We found that 13 % of waste pickers’ scavenged for food to use at home. This practice
is comparable to findings elsewhere. In a study done in Buenos Aires, Argentina, Parizeau
(2013) found that 61 % of waste pickers’ scavenged for food to eat. However, the food that the
waste pickers’ scavenged on was food that was set aside in separate refuse bags and were not
placed with the rest of the waste to avoid waste pickers’ from getting sick. Food that is put in
the same bags as other household waste is often a health hazard. In this study, some waste
13
pickers reportedly got sick from drinking milk that was discarded with all household waste.
The collection of food is essential to waste pickers’ because they need to survive (OtengAbabio, 2012), however there is need to ensure that such activities do not pose a health risk to
waste pickers.
4.4 Waste picking and poverty reduction
Table 1 shows the poverty incidence and poverty gap for household members with and without
waste picking income, using three poverty lines. Using the food poverty line, the findings show
that the proportion of poor people with waste picking income was 61 % but increased by 29 %
without waste picking income. Total annual income is reduced by more than three times from
ZAR3852 (USD367) to ZAR1215 (USD116) per household per year without waste picking
income. Poverty-gap analysis shows that on average no-one lived below the food income
poverty line but 68 % of the people would fall below the poverty without waste picking income.
Similar analysis using the lower bound poverty line and the upper bound poverty line yielded
similar trends.
Table 1: Poverty incidence (PI) and poverty gap index (PGI) with and without waste picking
income
Proportion (%) of
Mean annual
poverty line
(ZAR)
PI with waste
picking
income
PI without
waste picking
income
PGI with waste
picking
income
PGI without
waste picking
income
3852
61
90
0
68
14
people using the food
poverty line
(R321/month)
Proportion (%) of
people using the lower
bound poverty line
(R443/month)
Proportion (%) of
people using the upper
bound poverty line
(R620/month)
5316
77
92
28
77
7440
87
97
48
84
The results are suggestive of two aspects. First, waste picking income reduces the number of
poor people. Second, waste picking also cushions people from falling deeper into poverty;
hence waste picking could be seen as safety net for the urban poor. According to Gonzales
(2003), waste picking contributes poverty reduction, which is one of the major problems facing
developing countries today.
4.5 Determinants of waste picking income
We regressed various respondents and household variables (such as age, gender, education,
household size, frequency of waste collection and access to transport) against waste picking
income. The results are presented in Table 2. Fifty-six percent of the chosen variables were
significantly related to waste picking income. Overall, the regression model shows a significant
relationship between the chosen explanatory variables and waste picking income (F = 3.416; p
< 0.003). The model explains about 25 % of the variation in waste picking income. Gender of
respondent, household size, access to transport, frequency of collection and poverty status were
all significantly and positively related to waste picking income. Age and education of
respondent, standard income and hours spent in waste collecting activities did not yield any
significant relationships.
Table 2: Ordinary Least Squares (OLS) regression of waste picking income against socioeconomic variables
Variable
Expected
b*
Std. Err. of b*
b
p-value
sign
Intercept
-13081.8
0.318318
Gender
+
0.246462
0.143183
8729.9
0.091258*
Age
-
-0.053818
0.177451
-48.1
0.762909
15
Edu-Grade
-
-0.15952
0.156184
-642.3
0.311905
H-size
+
0.39014
0.12479
2723.5
0.002921**
Grant total
-
-0.070012
0.132582
-0.1
0.599743
Hours
+
-0.059117
0.149625
-330.7
0.694416
Transport
+
0.254392
0.134125
7782.9
0.063541*
Frequency
+
0.281548
0.135997
2419.7
0.043511*
Poverty status
+
0.509091
0.120522
15416.1
0.000099***
***, **, * Represent 1%, 5% and 10% levels of significance respectively.
With regards to gender, there was no significant difference in waste picking income between
males and females (p> 0.05). The results, though not statistically strong, seem to suggest that
men were likely to extract more income from waste-picking activities than females because
of the energy and strength required to lift and transport heavy material from the dump and
streets to the merchants’ place of business. Household size was significantly and positively
related to waste income perhaps due to waste pickers having to support more dependants.
Waste pickers with access to transport was more likely to tap more from waste picking
activities obviously because they were more likely to transport more waste than those who
carried waste on their heads and backs. A higher frequency of waste collection was likely to
result in higher income from waste picking because of the likelihood of collecting large
quantities of waste. The poverty status dummy shows that poor waste pickers were likely to
have more income from waste – perhaps because for most of the poorest of the poor, waste
picking is often the only source of livelihood. Results from a study done by Nzeadibe et al.
(2012) in Nigeria showed that 80% of waste pickers would stop waste picking if other
sources of employment were available. Similar to our findings, these results show that many
people engage in waste picking due to the lack of sufficient alternative employment.
Households with other sources of income such as grants have other options to fall back on for
example part time jobs and remittance. However, as noted above, our regression explains
only 25 % of the variation in waste picking income. This seems to suggest that other
household factors and those beyond the control of the waste pickers could have an influence
on waste picking activities. For example, weather, unsorted waste, protective equipment, as
well as the health of the waste pickers themselves and lack of institutional support from the
government and other stakeholders may affect the amount of waste collected.
16
4.6 Waste pickers’ perceptions on challenges encountered
More than half (62 %) of the waste pickers said they encountered constraints in their waste
picking activities. The respondents mentioned cuts on their fingers (due to lack of protective
wear) which often led to infections, the bad odour coming from mixed wet degradable and
non-degradable waste in refuse bags and at the dumps, ‘bad’ weather and lack of transport as
some of the main challenges. Other respondents said they had problems with scavengers (dogs
and animals) that ripped apart waste bags before they collected waste. They said that they are
often wrongly blamed for littering streets yet it is the scavengers responsible for littering. Some
waste pickers’ also said that some residents threatened them and perceived that that dog owners
deliberately released their dogs on them similar to findings by Nguyen et al. (2003).
When asked what could be done to improve their plight, 76 % cited provision of jobs and the
rest proposed transport for moving their waste. The need for jobs highlights that most people
in the waste picking do so not by choice but as the last option. It may be that the working
conditions are also not good hence waste pickers would opt out of waste picking if better
alternatives were offered. We also asked waste pickers’ perceptions on their contribution to
local Makana Municipality’s waste management services. More than half 55 % of waste
pickers perceived that they were helping the municipality.
5. Recommendations and conclusion
Is waste picking trash or treasure? The findings of this study show that waste picking is a key
livelihood source for the urban poor. This is because it prevented waste pickers’ from falling
deeper into poverty. However, it seems that the potential of waste picking as a poverty
reduction strategy could be enhanced if waste picking is formally acknowledged and supported
as a viable income generating activity. The general public need to be educated about waste
management and awareness needs to be created in the form of workshops, focus groups and
programs. Through education, negative perceptions of waste pickers’ will be reduced and the
community will be more inclined to be active participants in sorting their own waste. This will
contribute to improving the waste pickers’ working conditions and potential income. Waste
pickers’ have a positive influence on sustainable waste management which is one of the main
problems faced by developing countries (Gonzales, 2003). For example waste pickers’ collect
around 50-100% of recyclable material in many developing countries without cost to the
17
municipality (Sharholy et al., 2008). The price of recyclable waste needs to be negotiated
among the recycling stores and waste pickers to reduce exploitation and increase their
bargaining power. The municipality needs to consider providing protective gear, transport,
health care services and compensation for services rendered for the removal of waste (Adama,
2014).
Langenhoven and Dyssel (2007), who did a similar study in Durban, found that people within
the lower income bracket engaged in waste picking as their way of raising household income.
The main challenge is the lack of formal recognition across the waste management hierarchy
which creates a platform for exploitation (Adama, 2014). To address this problem waste
pickers’ need support from the municipality and interested stakeholders to allow alliances to
be formed. For example, Colombia, in South America, has the oldest and most successful waste
picking organisation in the world (Medina, 2000; Medina, 2007; Adama, 2014). Through these
alliances self-esteem and social status can be enhanced which may give waste pickers a higher
bargaining power when dealing with merchants (Adama, 2014). Income of the waste pickers’
may increase which could result in an improved quality of life. Waste pickers’ in South Africa,
could gain empowerment through the formation of unions. For example, in South Africa, waste
pickers’ from across the country gathered for The First National Waste Picker Meeting in 2009
which shows the potential for waste pickers’ to form alliances (Adama, 2014). This could
improve their bargaining power when dealing with merchants and could allow them to compete
economically. For example, once unions have been established, waste pickers can start to bid
for tenders to collect and sort waste which helps avoid the middle man (the merchant) and
improve the market value of waste. This is difficult to achieve without multiple actors involved
in the tender acquisition process. Middlemen are able to buy waste materials as they form a
connection between waste pickers and the waste industry (Nzeadibe et al., 2012). In a nutshell,
waste picking has the potential to become one of poverty alleviation strategies in small to
medium sized cities. However, to realise its full potential, waste picking needs proper
recognition and sustained support from not only the municipalities but also from the public.
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