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Hspa - Research Methods Paper Guidelines

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Each HSPA student must demonstrate the ability to use appropriate doctoral-level research methods by submitting an empirical research paper. The paper must be approved by the student's advisor and the HSPA research methods coordinator (currently Professor Will Dow). This requirement must be met before the student can take the oral qualifying examination.

There is considerable flexibility in the research paper requirement, depending on each student's area of interest and expertise. The paper could be an independent project exploring a potential thesis topic, could build on a class term paper, could be part of a research project conducted with a faculty member or as part of a job, or anything else acceptable to the adviser and methods coordinator. There are no bounds set on types of methods or data used, however it is recommended that the student consult the advisor and methods coordinator early in the process.

The key expectations are:

Use actual empirical data to explore an interesting question in the field of HSPA.

Use methods appropriate for a researcher trained at the Ph.D. level.

Write a paper of potentially publishable quality.

Typical Structure

The following is an outline of the structure of a typical methods paper, although individual papers may vary considerably from this structure. Text is 10-25 double-spaced pages, 1" margins, 10-12 point font.

1. Title page

Title, name, date.

Short abstract (structured or paragraph).

In a footnote acknowledge anyone who has made important contributions to the paper.

2. Introduction (1-2 pages)

Explain the broad question and motivate why it is interesting.

Outline the hypotheses that you will be testing, and discuss how they will inform the broad question.

Relate your paper to any important previous studies that you have built on (complete literature review not required).

Conceptual framework

Provide a conceptual framework for considering your question, and state the exact hypotheses to be tests.

3. Data

State the exact source of data. Describe the data's population and sampling design, particularly complex survey features such as clustering and weights.

If using a sub-sample of the data, describe the exact selection rules so that another researcher could replicate your sample



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