Ontology, Epistemology, and Methodology

Three Central Concepts

• Ontology concerns the nature of reality and existing phenomena
  • Social structures exist independently of individuals versus society as a sum of individual actions is an example of ontology.
• Epistemology addresses the nature, sources, and limits of knowledge
  • Whether knowledge is objective or context-dependent is an example of epistemology.
• Methodology outlines methods and techniques used in research
  • Using quantitative surveys or qualitative interviews is an example of methodology.

Scientific Perspectives

• Positivism emphasizes objective, measurable facts, building on empirical observations and scientific methods
  • Statistical analysis of income's impact on education exemplifies positivism.
• Empiricism posits knowledge as built on observation and experience
  • Researchers aim to minimize subjectivity through systematic methods
  • Surveys on voter behavior and quantitative analyses of voter turnout represent empiricism.

Inductive vs. Deductive Reasoning

• Inductive reasoning starts with observations, leading to theory
  • Students in small classes perform better, leading to theory about classroom size influence on learning.
• Deductive reasoning begins with a theory, tested with data
  • Hypothesis stating higher income leads to higher education is tested through statistics.

Research Paradigms

• Scientific realism suggests reality exists independently of perception
  • Models for global power shifts exemplify this.
• Interpretivism views social reality as subjective, shaped by individual perceptions and experiences
  • Studies of how political leaders create narratives to legitimize power exemplify interpretivism.
• Critical realism posits that both structures and actors influence reality
  • Institutional frameworks impacting election campaigns, while campaigns can alter norms.
• Constructivism frames reality as socially constructed, dependent on cultural and historical context
  • Varying definitions of "democracy" across societies exemplify this.

Objectivity and Values in Research

• Positivism advocates for value-free research, but critics argue a researcher's choices and background always influence
  • Studies on climate change influenced by the researcher's view on economy versus environment exemplify influence.
• Reflexivity involves researchers analyzing their impact on research
  • Researchers maintain a research journal or have colleagues review the work to analyze their impact

The Research Process

• A research problem should be relevant, specific, and researchable.
  • Sources include theoretical gaps, practical societal issues, and prior research
• Research questions should answer: What? How? Why?
  • Types include descriptive (what happens), explanative (why it happens), and normative (how it should be).
• Good research questions should be clear, specific, related to the research problem, and empirically investigable.

Refining a Research Question

• Important factors include relevance, connection to current developments, time frame, context, and data availability.
• Otydlig: How should governments handle corruption?
• Fokuserad: What institutional mechanisms reduce corruption the most in democracies?
• För bred: What affects the public opinion?
• Fokuserad: How is public opinion affected by disinformation campaigns on social media regarding immigration in the USA?

Literature Översikten

• Identify knowledge gaps, place research in a theoretical context, and show researcher familiarity
• Literature review steps involve mapping the data, analysis of quality of studies, and then synthesis of results

Connecting Theory to Research

• Guide including formulating hypotheses and explaining/interpreting results
• Three approaches
  • Deduction: from concept to conclusion
  • Induction: from conclusion to concept
  • Abduction: Combination, interpreting unexpected results from theorie
• Risks include theoretical bias like preconceived ideas and cherry-picking data

Hypothesis

• Assumption about the relationship between two variables
  • Must be testable and clear
• Examples of types of hypotheses
  • causal
    • "Increased unemployment leads to increased support for radical right-wing parties."
  • correlation
    • "There is a connection between education and environmentally conscious behavior."
  • null-hypothesis
    • "There is no difference in political participation between women and men."
• Test
  • Data analysis and collection
  • Statistics used to confirm or deny

Mistakes

• Too broad: "Education affects politics" - use "Higher education reduces the likelihood of support to authoritarian parties."
• Not testable: "Politics is always affected by culture." - use "Countries with proportional election systems have a high level of female representation"
• Vague variables: "Economic policies affect well-being." - use "Increased public spending in healthcare leads to fewer hospitalizations

Research Design

• Definition - A plan for how research can be used to answer research questions
• Components
  • Setting clear goals
  • Choosing methods for collecting data
  • Identifying timing

Research design Types

• Exploration - using new phenomena with limited existing knowledge
  • Uses interviews
• Describes - mapping and describin gphenomena
  • Usually uses charts
• Explanation - explains casual relationships
  • experiments or Longitudinal examples

Opertationalising

• Making concepts more testable
  • Can change measurement of data by change indicator

For example:

• concept - political activity
• measurement - level of voting, memberships and demonstrations

Validity

• Can the study be universally measured?
• Can the results be generalized?

Reliability

• Are the result measurements

Triangulation

• Using multiple methods in order to show reliability

Data collection and analysis

• Data collection is using information questions
• Types of information
  • Primary- collected by researcher
  • Secondary- Pre-existing collection
  • Big - very data sets using digital collection
• Types of data collection
  • Qualitative- looks at text and images or sounds
  • Quanitative- Uses statistics data

Data collection criterias

• Validity - is teh data acurate?
• Reliability - are teh data consistent and reproducible?
• Objectivity- avoid biases
• Ethical considerations- protect the personal integrity

Collecting

• Metods
  • Observations of nature
  • Interviews for understanding
  • Surveys for quantitative measurement

Methods for analysis

• Qualitative analysis focuses on thematical analysis and coded
• Quantitive analysis uses statistical models and correlations

One study/case study

• A analysis of an event or orginiation for example

Strengths

• Deeper insights
• Grasping complexities of contexts

Weaknesses

• Generalization is difficult
• Risking results is subjective

Types of one study studies

• Descriptive - documenting an event
• Explanatory - identifying a case
• Utforskande - discover and research a case outside a certain area
• Comparactive - looks at a wide area to identify case parameters
• Longitudinal - Study one case in time, to analyze evolutions

Process tracing

• Analyzing causal relationship through analyzing events

Elements

• Describing the event, understanding the relationship

Example

• An economical criss leading to political instability

Comparisons

• Systematical analysis to better study case

Goal

• Identify variable between cases
• test assumptions

Exampels

• Populism within Europe. Comparisons between Sweden and Hungary
• Developments within leadership, from certain areas

Methods In comparison

• Looking at differences between systems and designs
• Similar system designs
• Comparing a normal to a outliner
• Analyze changes to institutions and regimes

Methods

• Analyzing long time changes of institutions
• Main concept is Path dependence - where the original choice has a effect of future developments

Method for both quantitative and analytic

• This will result in a bigger picture, with a deeper understanding for both sides
• Qualitative will bring insights
• Quanitive focuses statisticle results

Analys metod

• Fallstudie = deep dive in one area
• Comparisons = more general knowledge

Information gathering

• Qualitative research that looks at organisations, or societies
  • Structured
    • same information to everyone
  • Unstructured
    • open-ended information with a improvised atmosphere
  • Semi-structured
    • both sides
  • Expert interview
    • only talking to experts in the area
  • focus groups
    • group discussions
  • online conferences
    • talking to a limited number of people

Steps to have a good interview

• Have a opening
• build trust
• always prepare

Stages after interview

• Data minimize
• Reorganise
• Interpret

After the interview

• Tag and compare the text

Challanges for reviews

• Hard to show results
• Risking subjects
• time-consuming

Observations

• Direct data by reviewing interactions in the area

Purpose

• Knowing dynamic inside people

types

• structured- limited categories
• unstructured - free in form

Ethics

• Always a review from a Ethical standpoint
• Always be anonymous

Benifits

• deeper insights of a natural event
• can be a compliment of other materials

Challenges

• Always focus on the observers eye

Texts

• Analysing in order to connect communities

Analytics with contents

• Quantitive ways that ideas come into texts.

Areas

• How media represents
• How is media changed

Ways

• Understand and determine analytics

Text analys

• Understand key facts and figures with the subject

Types of text

• Descriptive (looks at the sources)
• Descriptive (seeks for the facts) Critical (sees if it is logical)

Methods

• Identify types for compare

Models in text

• Always be aware of the culture
• language is not neutral
• meaning is only created within discource - structures influence identities
• always be aware of power within discourse

Discourses

• Knowledge is created from speaking and discourses

What is one diskurs?

• How the media shows and presents stories
• What the effects are from events, like climate change
• Language is used in order to get a end goal

How a discourse effects our knowledge

• Power controls language
• Political campaigns mean language

Discourses are frameworks

• Diskurs equals knowledge

There are power behind a discourse.

• There is also discourse around what we already have

Methods

• Is the information allowed to spread, whats right

Analysis in relation to discourses

• To analyse changes from historical discourse, you should follow the theory of power
• Key persons =Lacau, Mouffe,
• How to spread
• Key concepts
• how a picture is shared.

diskurspsykologi

• Wetherell & Potter
• focus is how individual using discourses in the interview

wpr -approach

• Analyse how social problems are constructed in politics
• Important questions are for example, how representative is media and effects are made.

Qualitive Methods

• Focus on quantitative method vs qualitative

Key to understand quantitative data

• measuring how a subject is created
• analyse the data
• using existing and deep theories

Quantitive analysis

• How much is one element?
• Results can always be generalized
• the amount of results
• use of statistics

Data-set can be broken down by

• What information to collect
• what parameters to change

Data-matrix

• All data from a diagram is known as variable data.

Type of variable

• Diskret- that is clear an understandable
• continuous - can be anything but can be something
• The main goal is to understand the scale

Measure scale

• No-mean scale = gender of a group
• Ordinal scale. = school level
• absolute Nollpunkt (kvotskala)

Collection

• Methods are using questions (standardized questions), Experiment and statistic
• Make abstract data collected as a variable

Data is collected in multiple ways

• Medium, Mode,
• Range
• Standard - why do datas differ from other variable

Stats

• Stats in description and central point
• Conclusion of data to be able to be explained

Relations between variabes

• Studying different data is studying levels
• depending of gender, will affect the results + and

Data will present levels for you depending on

• Beroende vs oberoende

Regression

• The main purpose is to get what the data looks like
• In regression it says what effects, there could be many effects

Always have proof that the variable is the same from the start.

Quantitative Methods II

Pictogram

what our data is and how it has been

Test Theory

probability test

Test Methods

• Statistical way to see whats good

Average Method

• Average to test that is made

Probability distribution

• what percentage can be used for test

The result

• Try with some methods and write it down

Testing and hypotes

• what test has been made

Statistic analysis

• Signification

Testing and variables

• Test with some methods and results