LITERATURE REVIEW, CAUSAL THEORY/LOGIC MODEL 3
According to the above model, the variables that can be identified include the immigrants
that should be permitted into the country annually, the number of children that each immigrant
has, the highest level of education attained by the parents of kids that were previously covered by
the DACA program, political factors such as parties and policies, and lastly, the home or initial
place of residence of the immigrants. Apparently, the factors can be represented in a simple logic
model that can also be used to establish causal relationships amongst the variables. According to
the Kellogg Foundation’s “Logic model development guide,” logic modeling significantly
improves the participatory role and makes evaluation more useful as an approach for management
and learning (2004). In order to develop a working or practical logic model, one should be able to
identify outcomes and anticipate the best ways of measuring them to offer participants of the
program and a clear roadmap regarding the exercise. However, causal relationships can be
discussed before fitting the variables, activities, outcomes and outputs in the logical model.
For instance, the issues surrounding the DACA program point to the causal relationship
between the number of illegal immigrants sneaking into the country and the policies put in place.
Specifically, the squabble between Democrats and Republics evidently emanate from the high
number of immigrants and their children that need to be registered under the DACA programs.
Again, the more the immigrants that enter the country the more stringent policies are put in place
by the government.
Furthermore, a causal relationship exists between the level of education of the parents of
the DACA kids and possible ending of the program. For example, educated immigrant parents
understand the legal procedures and avenues that need to be followed to get documented and
legally register their kids. In addition, such educated immigrant parents clearly understand the risks