Section 6 : Limitations and Opportunities of the Data
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The next step provides an estimate to the number of Dominicans who turned out to vote at the voting polls. However, there was no voter registration or turnout information publicly
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available through the website denoting any type of ethnic or racial categorization at a congressional district level. The website did provide information at the county level.
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Hudson was the only county that was shared by Rep. Rothman of District 9, Rep. Payne of District 10, and Rep. Menendez of District 13 in the 108th Congress.
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Table 12: Basic Population and Voter Constituency Estimates for Hudson County, NJ
| Hudson County |
Value |
| Total Population |
608,975 |
| Total Voter Population |
351,622 |
| Latino Population |
242,234 |
| Latino Voter Population |
105,976 |
| Dominican Population |
28,520 |
| Dominican Voter Population |
8,767 |
| % Latino Voter / Total Voter Population |
30.1% |
| % Latino Population / Total Population |
39.8% |
| % Dominican Population / Total Population |
4.7% |
| % Dominican Population /Latino Population |
11.8% |
| % Dominican Voter Pop / Latino Voter Pop |
8.3% |
| % Dominican Voter Pop / Total Voter Pop |
2.5% |
| Registered Voters 6/02 |
279,722 |
| Voter Turnout 6/02* |
55,627 |
| Estimated Dominican Voter Turnout (@2.5% of Total Voter Population) |
1390 |
| Registered Voters 11/02 |
284,024 |
| Voter Turnout 11/02* |
105,483 |
| Estimated Dominican Voter Turnout (@2.5% of Total Voter Population) |
2,637 |
Data source:
2000 US Census Bureau, Summary File 4; New Jersey Division of Elections
| Table 12 lists some of the key findings on Hudson County, New Jersey.
Here the same pattern is illustrated as in Table 11 with regard to the relative
Dominican population and its sizeable percentage as a potential voting cohort among
the Latinos of Hudson. However, it is difficult to discern how these votes should be
distributed to each of the congressional districts (9, 10 and 13) without further study.
To be able to obtain the desired level of detail it would demand a significant level of
investment and resources that are currently beyond the scope of this study.
As such, this limitation is a potential opportunity for further research in the future.
Box 2 provides some highlights of other options that may be possible in determining
registered voters and turnout in the future.
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Box 2: Other Options for Determining Registered Voters and Turnout
Other methods of determining registered voters and voter turnout are available.
Another way to estimate registered voters is by using a mapping technique.
This was a strategy used by the Hispanic Federation in their recent Voter Participation study.
Researchers within the Dominican community are trying to employ this technique in other areas.
For instance, the Dominican Studies Institute is using this technique to
determine the HIV/AIDS population among Dominicans in the City of New York.
Here, too, a cost-benefit analysis needs to be done to assess the viability
in using this data for the top 100 electoral districts with the most Dominicans in the nation.
Voter turnout can be measured through the use of "exit poll" data, if it can be found.
With the "exit polls", there is the idea that the sample used by the poll sponsor conducting
the exit poll is too general (with a very small sample), and they only focus on competitive
congressional races. If the exit polls information is available in some congressional districts
there is a high cost involved to buy it.1 Given the expense, it is important to consider the cost,
benefit, and need of this data.
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However, politicians could be more strategic in their approach to Dominican constituents.
Primarily, they could support the gathering of ethnic-specific information during registration
and in other information gathering opportunities. Since some of the concerns outlined may
not explicitly be Dominican-focused per se, this also offers a good opportunity for the
Dominican community to do coalition building within other ethnic-minority group that can
benefit from ethnic-specific and redistricting-specific information.
Estimating Population Projections
As with the voter registration calculation it was our goal to report highly specific
population projections with the use of the cohort II methodology. However, there was a
surprising lack of ethnic specific data, even in New York City, were Dominicans most
commonly reside. In particular, ethnic specific fertility, mortality, and mobility
rates for Dominicans were sought.
While the information may exist, it was not easily
available to the general public.
New York City’s Department of
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Health does publish
an annual Vital Statistics summary document, but the data presented is just reflective
of the current year. Thus, in order to obtain further ethnic-specific information,
more time and resources would be required. Moreover, as the Dominican community
grows and expands, the data to be obtained in New York City is simply insufficient.
Ethnic specific data should be made available at a national level as is found with
other ethnic groups such as Mexican, Puerto Rican and Cubans. Thus, the need to
advocate to obtain Dominican-specific information is also an opportunity to enter
into dialogue with other ethnic groups so as to build coalitions and create a new
modus operandi with regard to the gathering of ethnic-specific information.
Summary
This section discusses the limitations found within the study and potential opportunities.
Firstly, the vulnerability of the adult citizenship calculation lies in the how the data would be
affected if corrected for misrepresentation.
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If misrepresentation errors are assumed to be committed
evenly throughout the congressional districts then the data would still be minimally affected.
However, if errors are regionally skewed then some congressional districts could have an
under- or an over-estimate of adult citizens depending on the location of the district
relative to the skewed geographic area. Secondly, while the estimated numbers of Dominican
registered voters and voter turnouts could not be determined nationwide,
Hudson County, NJ was used as a best approximation of what ideally this study would have
like to have achieved at the congressional district level nationwide.
Thus, the Hudson County, NJ analysis can serve as an ideal benchmark for what
policy makers and analyst should strive to surpass and perfect, respectively,
at a national level in terms of creating a space for determining and using
group-specific indicators. Lastly, the logarithmic formula was the best option
in the absence of group specific fertility, mortality and mobility rates.
However, the approximation formula starts to break down with time.
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