Workshop 1: Finding questions
Department of Political Science
School of Social Sciences and Philosophy
Trinity College Dublin
Violeta Haas
Assistant Professor in Political Science
New at Trinity College Dublin
Previously
Research How institutions and elites shape perceptions of and behaviour toward marginalized groups (esp. immigration & LGBTQ+ rights). Also party competition, social norms, (hate) crime, and protest.
Methods Causal identification & computational social science. Experiments plus multimodal LLM applications.
Workshops
Short submissions: (Mon 11:59 pm)
For each of the 2–3 broader questions/topics you brought, work through these points questions.
By December proposal should cover a draft of: Abstract + Introduction (RQ) + lit + theory + design.
A research question is one that:
Adapted from Halperin & Heath (2020), Political Research: Methods and Practical Skills (3rd ed.), ch. 4.
What do you think about this research question?
Does the colour of campaign posters predict which party’s volunteers smile more while canvassing?
Can be answered through conducting research with the available resources.
Feasibility check (early)
Methods can wait… doability cannot!
You must show that:
→ Locate your question in the literature (do not reinvent). Improving answers can mean being more systematic or bringing in new cases or angles.
Too broad
“Immigration and public opinion”
“Protest and politics”
“Hate crime and threat perceptions”
Concrete RQs the three articles pose
Hangartner et al. (2019): Does exposure to the refugee crisis make natives more hostile?
Haas et al. (2026): Do bystanders—citizens who observe protests without participating—change protest-related attitudes and behavior?
Dancygier et al. (2022): Do fears over mate competition drive anti-refugee hate crime?
Questions rarely appear fully formed. Common entry points:
RQ: Does exposure to the refugee crisis make natives more hostile?
How they got there
Motivation: major real-world event + causal identification gap
RQ: Do bystanders—citizens who observe protests without participating—change protest-related attitudes and behavior?
How they got there
Motivation: missing actor + imperfectly measured treatment (exposure to protest)
RQ: Do fears over mate competition drive anti-refugee hate crime?
How they got there
Motivation: event + overlooked discourse + theory transfer
Which hollow circle is bigger?
→ The surrounding circles change how big the hollow ones look, even when they are the same size.
Cikara et al. (2022) transfer this intuition to group threat theory: how threatening a minority group seems can depend on the size of other minorities around it (relative size rank), not only its absolute size.
Podcasts can be a surprisingly good place to stumble on a research question!
Example from my own research: I study how prohibiting a victim-blaming strategy in court can help reduce violence against minoritized groups. I first encountered it via the podcast Criminal.
Gap: We know a lot about bias and discrimination at policing, charging, sentencing,… Much less about what happens at trial
Criminal, Episode 129: “Panic Defense” (6 Dec 2019)
Dancygier, Egami, Jamal & Rischke (2022) — closing section
Dancygier et al. (2022) study male-heavy refugee inflows. Contemporary cases that flip or complicate the mating-market story:
(A) Ukrainian refugee inflows
(B) Rising LGBTQ ID among Gen Z women
(C) South Korea’s 4B movement
Adapted from Lipson (2018), How to Write a BA Thesis (2nd ed.), ch. 4.
Before we talk about how to take notes — what do you already use?
→ No single “correct” way, but you need some system before the literature grows.
Capture the main points of each article - Make sure your notes capture the heart of what you are reading, phrased in your own words (not a chain of quotes).
Useful Habit
write a short “My summary” that states the argument, the main evidence or claim, and what the authors reject or set aside.
A major source of plagiarism is not intentional cheating… it is simple mistakes caused by bad notes.
Main goal: a short map of the whole project.
Organisation: question → relevance & gap → theoretical argument → empirical strategy & data → (later) main findings → contribution & implications.
Does x cause y? Everyone agrees that this issue is really important. But we do not know much about this specific question, although it matters a great deal, for these reasons. We argue that X causes Y for these other reasons. However, we expect that this effect is importantly conditioned by Z. We test our theoretical argument using a fantastic new dataset across X countries and from 1945 until 2019 that we compiled using this cutting-edge method. Using innovative super modeling, we find that X really matters for Y which is an important finding for these reasons. Our findings have important implications for our understanding of how the world works and its role in the universe.
Source: Heike Klüver
Three abstracts, ≈150 words each. Capstone abstracts are prospective (present/future tense is fine).
See you on 8 October.
POU44000 · Workshop 1