6.3.5 Miscellaneous group
The 19 respondents from this group represent an eclectic mix of livelihoods and prosperity that were interviewed because they were connected to the fishing
industry. The majority of these respondents were former fishermen who had either retired, fallen ill or changed profession. Some of them continued to fish
occasionally but it was no longer a significant part of their livelihood portfolio. A brief explanation of the 19 is given below:
3 x fish agents: 2 of these were small scale operators buying small quantities of fish and the third was much wealthier, buying a large proportion of the whole of
Sungai Pinang’s catch. 3 x retired fishermen: Two of these were former bagan crew members, the other
still owned a small sampan. 3 x labourers buruh angkat: All of these used to work as bagan crew members
but for reasons of ill health or not receiving enough income changed to become fishing industry labourers. Mostly that entails moving boxes of fish, ice and other
fishing equipment around the harbour. 2 x motorbike drivers: Both of these were former bagan crew members who had
intentionally changed profession. One had saved enough to buy a motorbike which he used as a taxi to take children to school. The other used his motorbike
for transporting fish. 2 x farmers: One of these had worked 20 years as a bagan crew member and the
other continued to occasionally fish on a sampan. 2 x fishermen’s wives: Both of these women had husbands who used to be
fishermen. One of the husbands had died recently and the other had suffered a stroke.
1 x fish processor: He worked for a long time as a payang crew member before purchasing his own boat. His son bought the boat and now he processes the fish
that his son catches. 1 x diver: He uses a compressor and goes diving at night for octopus, sea
cucumbers and other shellfish. 1 x ship builder: He builds bagan ships.
1 x shop owner: For one year he has owned a shop selling fishing equipment and general supplies. Prior to that he had his own sampan but it fell into disrepair.
Figure 6.9:
‘Other’ scores from MDS projected on a bad 0 to good 100 x-axis for all six fields of the analysis. The y-axis shows the similaritydissimilarity
scores. Ag = fish agenttrader, Mo = motorbike owner, La = labourer, X = widow, Il = husband ill, Dv = diver, Ca = café owner, Pr = fish processor, Fm = farmer, Rt
= retired, Sh = ship builder.
In contrast to the other fishing industry sectors, scores in the natural field
in this miscellaneous category are on average higher Figure 6.9, top left panel. Rather than this effect being caused by having access to more natural capital, it is
predominantly a feature of these respondents not being fishers and so not being
Ag Ag
Ag Mo
Mo La
La La
X Dv
Ca Pr
Fm Fm
Rt Rt
Rt Il
Sh
-40 -20
20 40
20 40
60 80
100
Natural
Ag Ag
Ag Mo
Mo La
La La
X Dv
Ca Pr
Fm Fm
Rt Rt
Rt Il
Sh
-40 -20
20 40
20 40
60 80
100
Financial
Ag Ag
Ag Mo
Mo La
La La
X
Dv Ca
Pr Fm
Fm Rt
Rt Rt
Il Sh
-40 -20
20 40
-20 20
40 60
80 100
Institutional
Ag Ag
Ag Mo
Mo La
La La
X Dv
Ca Pr
Fm Fm
Rt Rt
Rt Il
Sh
-40 -20
20 40
20 40
60 80
100
Social
Ag Ag
Ag Mo
Mo La
La La
X Dv
Ca Pr
Fm Fm
Rt Rt
Rt Il
Sh
-40 -20
20 40
20 40
60 80
100
Human
Ag Ag
Ag Mo
Mo
La La
La X
Dv Ca
Pr Fm
Fm Rt
Rt Rt
Il Sh
-40 -20
20 40
20 40
60 80
100
Physical
able to complete attribute scores for ‘state of stocks’ and ‘fishing income’ which in the othe
r fishing sectors tended to be allocated ‘bad’ scores. The scores for the natural field then became dependent on the attributes natural disasters and ‘access
to land resources’. As supplementary livelihoods, nine of the 19 respondents
farmed rice, two of these also had livestock and one of them also owned a shop. Of the remaining ten, one kept buffalo and one farmed catfish in ponds
constructed from tarpaulin at the rear of his house. Four of the 19 respondents from this sector had previously lost a fishing boat because of bad weather.
In the human field, the ingenuity and perseverance of some of the
respondents was remarkable. From all interviewees across all sectors, only 23 reported that their wives contributed directly to the livelihood portfolio of the
family. However, in situations where the husband was no longer able to go to sea and the children were still financially dependent on their parents this forced the
wife to work. One woman whose husband had a stroke 5 years ago has since worked processing fish, ironing and washing clothes to make ends meet. Several
of the respondents in this group had been prepared to take a risk in changing profession from being a crew member to starting their own small business. Two of
the three fish agents had formerly owned bagans and, having lost these through either a storm or bankruptcy, had shifted to trading fish. Both the agents and the
fish processor commented that good relationships with the catching sector are the key to successfully trading fish. The entrepreneurial nature, work ethic and
commitment to save of agents, processor, café owner and ship builder meant that they scored highly in the human field. However, there was a group of 8
respondents including the retired crew members, farmers, labourers and a recently widowed bagan crew member’s wife who scored less well in the human field
Figure 6.9, bottom left panel. None of these ever saved, reporting that incomes were just enough to survive each day, and five of them stated that they were too
afraid to borrow money to start a business because they might not be able to pay it back. For them, aspects of risk aversion and low self confidence may be a greater
hindrance to livelihood resilience than access to credit. Three of this group relayed the stories of how they used to work as crew members on bagans but due to ill
health, both mentally and physically, had been unable to continue. This
component of ill health relates closely to both the human and financial fields and could deserve an attribute in its own right.
In the financial field, the group of agents, the café owner and the ship
builder again scored higher than the group of labourers, farmers and retired fishers Figure 6.9, top right panel. This first group who owned their own businesses
were confident in handling money, saved regularly and each had diverse income sources. One of the agents told the story of how he and ten others had borrowed
300US from a local bank in 1995. Of the original borrowers only he paid the loan off in full and subsequently borrowed increasingly large amounts. He has just
finished off paying his recent loan of 10,000US and is planning on borrowing more. While access to finance credit to kick-start a business is one livelihood
strategy employed by members of this higher scoring group, several others reported that that they did not want to borrow formally because they were afraid
of not being able to pay it back. Their businesses had been built either on savings or on informal credit from family members that did not have a prescriptive
repayment arrangement. In contrast to the agents, each of the labourers and retired fishers reported that they had no collateral and could not imagine being able to
borrow financial credit from anyone, even family members.
As in other sectors, the institutional field scores poorly, regardless of the livelihood portfolio Figure 6.9, middle left panel. Similarly the social field was
low scoring with several respondent describing the decline in ‘neighbourly concern’ that occurred compared to past times Figure 6.9, middle right panel.
Across all fishing sectors responses to the attributes pertaining to trust, cooperation and equality had been generally negative but this was especially
apparent in the miscellaneous group. Only one of the 19 interviewees believed that a fishers group could operate smoothly and the remainder commented that
people work on their own and cannot work together. The agent who had been the only one to repay his bank loan used that experience of evidence that people think
short term and irresponsibly. A further respondent argued in the same vein, using the example of a government program that supplied cows as aid to Sungai Pinang.
The intention was for the cows to give birth and then for the cow to be given on to
someone el se as a ’revolving fund’. In reality, the cow was sold by the first owner
who took the profit for himself.
In the physical field, the same general pattern was apparent of a higher
scoring group including agents and the processor, and a lower scoring group of retired crew, labourers and the widow Figure 6.9, bottom right panel. The agents
and processor scored highly because they owned trucks and motorbikes for transporting the catch and equipment for processing fish. Two of them also used
their homes for the additional businesses of catfish farming and a general supplies shop. In contrast labourers and retired crew tended to have few physical assets.
Several of the attributes for the physical field could not be completed by respondents because the survey had been designed specifically with the fishing
sector in mind. So, for example, for farmers, shipbuilders and motorbike drivers, questions about fishing gear, processing of catch, selling at a an auction and
whether or not ice was required were not appropriate. Leverage analysis demonstrated that the attributes having greatest
influence on the scores were ‘state of coastal resources’, ‘state of land resources’ and ‘natural disasters’Figure 6.10. All other scores were below 10.
Figure 6.10:
Leverage exerted on the x-axis scores by each attribute for the ‘other’ group.
5 10
15 Geographical_isolation
Sheltered_mooring State_of_coastal_resources
State_of_land_resources Natural_disasters
Fishing_income Ability_to_save
Collateral Origin_of_loan
Goods_on_credit Savings
Remittances Alternative_income
Desire_to_save Market_awareness
Hard_working Occupational_multiplicity_skills
Risk Wife_working
No_of_children Education_aspiration
Education_reality Retirement_planning
Household_expenditure Husband_spend_consumables
Extension_officer Village_interventions
Personal_interventions Advocacy
Training_empowerment Community_spirit
Trust Leadership
Help_when_crisis Right_to_speak_out
Sanctions_rule_of_law Boat_ownership
Fishing_gear Other_asset_owned
Processing_adding_value Ice_availability
Housing Fish_auction
Natural Field
Instit. Field
Social Field
Finance Field
Human Field
Physical Field
6.3.6 Comparison between all sectors
Kategori