Sociology research methods

1. Introduction

• Sociologists use research methods based on the subject and research goals

• The credibility of findings depends on the research methods

2. Two Main Research Perspectives

1. Positivism (scientific, macro-approach)

2. Interpretivism (subjective, micro-approach)

3. Focus of Positivism

• Uses quantitative data (numbers, statistics)

• Sociology should be like natural sciences - human behaviour should be studied like natural sciences

• Emerged in the 19th - 20th centuries

• Key theorists: Comte, Durkheim

• Belief in “laws of social behaviour”

4. Positivism and Reliability

• Research must be repeatable and produce consistent results

• Methods should allow for replication

=> Reliability

5. Positivism and Objectivity

• Aims to avoid bias for accurate results

• Critics argue that complete objectivity is difficult

• Research is influenced by personal values

6. Preferred Research Methods

• OS - Official Statistics (government data)

• Questionnaires (quantitative surveys)

7. Positivism and Trends

Identifies how things change over time (e.g., decline in religious belief)

1.1B - Sociological Approaches and Research Methods

1. Durkheim’s Study on Suicide

• Main Idea: Human behaviors are governed by social forces (laws, values, customs).

• Key Findings:

  • Suicide rates within a country remain stable but differ between countries.

  • Social forces (e.g., family values, religion) influence individual actions and suicide rates.

• Methodology: Used positivist scientific methods, looking for correlations and causation.

2. Correlation and Causation

• Correlation: Two variables change together (e.g., low religious control → high suicide rates).

• Causation: One variable directly affects another (e.g., working more hours → earning more money).

• Durkheim’s Findings: Religion reduces suicide rates by fostering social connections.

3. Interpretivism Approach

• Focus: Individual actions and meanings rather than large-scale societal patterns.

• Key Concepts:

  • Social actions: The things people do.

  • Motivations: Why people act the way they do.

  • Verstehen (Weber’s Concept): Understanding people’s perspectives by “stepping into their shoes.”

• Research Methods: Prefers qualitative data (e.g., interviews) over quantitative statistics.

4. Research Methods and Validity

• Interpretivists Prefer:

  • Open-ended interviews to understand motivations behind actions.

  • Validity (how well research reflects reality) over reliability.

  • Subjectivity: Accepts that researchers’ personal perspectives may influence research.

5. Triangulation in Research

• Definition: Combining multiple research methods (both qualitative and quantitative) to improve validity and reliability.

• Strengths:

  • Provides deeper insights (e.g., combining surveys with interviews)

  • Allows cross-checking of data for accuracy

• Limitations:

  • Time-consuming and expensive (practical advantage)

  • Requires expertise in multiple research methods

  • Difficult to balance positivist and interpretivist approaches

6. Longitudinal Studies

• Definition: Research conducted over long periods (e.g., every 7 years).

• Example: Government census (collects data on household, religion, employment).

• Panel Studies: The same group of people is studied over time.

• Challenges:

  • Participants dropping out reduces representativeness.

1.1C - The Analysis and Evaluation of Research Choices - Hawthorne Effect

1. Bias in Research

• Bias may originate from a researcher’s values - beliefs and opinions (e.g., political views)

• Positivists argue that research should be neutral and objective, ensuring results remain the same regardless of who conducts or analyses the research

• Interpretivsts argue that complete neutrality is impossible since sociology is about people and human values

2. Causes of Bias

• Even choosing a research topic is influenced by the researcher’s values

• People, including researchers, tend to investigate subjects that interest them

3. What Should Researchers Do?

• Researchers should be honest about their biases so that readers can assess the validity and reliability of the research

• Many feminist researchers openly acknowledge their biases (tend to use interpretivist, non-scientific research methods)

4. Researcher Imposition

• The way questions are worded can lead participants to answer in a certain way

• The way data is analysed may also be impacted by the researcher’s personal biases

• Researchers may impose themselves or their values on participants

5. Interpreting Data

• Research findings must always be interpreted, making it important to recognise potential bias

• Both interview effects and the Hawthorne Effect influence research outcomes

6. Hawthorne Effect

• Origin: Discovered in an American factory where researchers attempted to increase worker productivity by changing variables (e.g., temperature, lighting)

• Findings: Regardless of changes, workers improved productivity simply because they knew they were being observed

• EXAMPLE: Both students and teachers may change their behaviour when they know they are being watched

7. Validity and Reliability in Research

• Validity: How accurately research shows the true picture - Interpretivists, Quant. Methods

  • High-validity methods: Participant Observation (PO), Unstructured Interviews (provide detailed, in-depth information)

  • Limitations: These methods may allow participants to mislead researchers or provide false information (participants are affected by the ‘Interviewer Effect’)

• Reliability: Whether research can be consistently repeated with the same results

  • Difficult in sociology, but can be improved through standardised procedures

8. Standardized Procedures

• Ensures participants are treated consistently, improving reliability.

• Example: Questionnaires with closed questions (fixed response options).

9. Reliable vs. Valid Methods

• More reliable methods: Questionnaires & structured interviews (favoured by positivists).

• Why is it more reliable? Use of standardised questions.

• Issues: Lack of flexibility, limiting deeper insights.

10. Representativeness & Generalizability

• Representativeness: The extent to which a sample accurately reflects the target population.

• Generalizability: Applying research findings from a sample to a larger group.

• A smaller sample must have the same proportions of different social groups (e.g., gender, ethnicity) to be generalizable.

11. The Interviewer Effect

• The interviewer’s characteristics (age, gender, ethnicity) may impact responses.

• Interviewees may adjust their answers due to:

  • Wanting to create a certain impression.

  • Avoid offending the interviewer.

  • Feeling judged by the interviewer.

• Similar to the Hawthorne Effect, where behaviour changes under observation.

12. Key Difference Between Sampling & Generalizability

• Sampling: Selecting a smaller group from the target population.

• Generalizability: Research findings applying to a larger group.

• A sample must be representative for the findings to be generalizable.

• Generalizability is sometimes limited due to practical issues

1.1E - Summary of Notes on Types of Data and Evidence Used by Sociologists

1. Differences Between Primary and Secondary Data

• Primary Data: Collected firsthand by the researcher through:

  • Questionnaires

  • Interviews (structured/unstructured)

  • Observations (PO)

• Secondary Data: Pre-existing data collected by other researchers or organizations.

  • Researchers often study published research before conducting their own.

  • Secondary data can support primary data or help develop new knowledge.

• Examples:

  • OS (government/official organizations)

  • Research by other sociologists, journalists, government

  • Media sources (TV, radio, newspapers, magazines)

  • Qualitative sources (historical/ personal documents)

2. Strengths and Limitations of Primary and Secondary Data

• Primary Data Strengths:

  • The researcher controls validity/reliability.

  • Designed for a specific purpose

  • Data is recent and relevant

• Primary Data Limitations:

  • Can be influenced by interviewer bias

  • Practical issues

• Secondary Data Strengths:

  • Easily accessible, often free

  • Accumulates knowledge over time

  • Useful when primary research is difficult due to ethical or access issues.

• Secondary Data Limitations:

  • May be outdated

  • Hard to assess reliability and accuracy

  • Data might be biased and lack validity

3. Qualitative vs. Quantitative Data

• Qualitative Data (Descriptive, literary, visuals):

  • Focuses on descriptions rather than numbers.

  • Often in written or visual form.

  • Used to describe events and experiences.

  • Favored by Interpretivists (Weber).

• Quantitative Data (Numerical, measurable):

  • Used for statistics.

  • Can be represented in graphs, charts, etc.

  • Favored by Positivists (Comte, Durkheim).

4. Strengths and Limitations of Qualitative Data

• Strength:

  • Respondent-led, reducing researcher bias.

• Limitations:

  • Hard to compare and analyze for patterns.

  • Difficult to identify trends.

5. Strengths and Limitations of Quantitative Data

• Strength: 

  • Reliable - standardised procedures

  • Objective, neutral, unbiased

  • Large sample size => generalizability

  • Presented in visual form

  • Comparisons

  • Easier to identify patterns/ trends

• Limitations:

  • Lacks validity 

  • Does not achieve verstehen

  • ‘Terms’ (views) are usually imposed by the researcher

1.1F - Summary of Notes on Official Statistics

1. Overview of Official Statistics (OS)

• OS are a main source of secondary quantitative data.

• Produced by national and local governments.

• Widely used, numerical in nature, and generally reliable.

2. Hard vs. Soft Statistics

• Hard statistics: Produced by official bodies, accurate and objective (e.g., birth and marriage records).

• Soft statistics: Depend on decision-making (e.g., unemployment, crime stats). More subjective and changeable.

3. Strengths of Official Statistics

• Practical advantage: Easily accessible (often free and online).

• Reliable: Based on large samples and systematic research.

• Useful for comparisons and trend identification.

• Help governments and organizations plan policies.

• Ethical advantage: No direct harm to research participants.

4. Limitations of Official Statistics

• Lack of validity: Focus on numbers, missing context.

• Socially constructed: Influenced by interpretations and political bias.

• Inaccuracy: Stats may not be as complete or representative as claimed.

• Government-funded: This may be manipulated for political agendas.

• Limited scope: Might not include all the details a researcher needs.

5. Non-Official Statistics

• Collected by religious groups, charities, and policy institutes (think tanks).

• Can provide alternative insights into social issues (e.g., racism)

1.1G - Historical and Personal Documents in Research

1. Definition & Importance

• Provide qualitative data and first-hand accounts of past events.

• Help investigate societal changes over time.

2. Types of Historical Documents

• Personal Documents: Letters, diaries, personal accounts.

• Autobiographies: Published life accounts, may be biased.

• Secret Documents: Government or organizational records, some classified.

• UK Census: Conducted every 10 years, statistical results are public, and raw data is released after 100 years

• Other Documents: Financial records, wills, school reports, pupils' notes.

3. Validity and Limitations

• Concerns: May be biased, not representative, written with personal intentions.

• Verification: This should be cross-checked with other sources.

• Accessibility: Some are private and difficult to obtain.

4. Triangulation in Research

• Diaries can be supplemented with interviews and questionnaires for a well-rounded study.

• Triangulation: Using multiple research methods (e.g., diaries alongside interviews and questionnaires) to improve validity.

• Mass Observation Research (MOR):

  • 1930s study where participants' diaries were used as primary data but later became secondary data for future research.

5. Strengths & Limitations

• Strengths: High validity, first-hand insights (verstehen), descriptive details.

• Limitations: Unrepresentative, require cross-verification, may reflect personal emotions rather than facts.

6. Historical and Personal Documents

• Definition & Purpose:

  • Provide qualitative data, and secondary data, usually first-person accounts.

  • Used to investigate societal changes over time.

  • Type of personal document, e.g, social media posts (webpages, blogs/vlogs,...)

• Considerations & Limitations:

  • Validity: This may be biased, exaggerated, or subjective.

  • Access: Personal documents may be hard to obtain.

  • Representative?: Some accounts may not reflect wider society.

  • Social media can be considered a modern form of autobiography.

• Examples:

  • Anne Frank’s diary: A personal but historically significant account.

  • Autobiographies: Published accounts of people’s lives but can be biased.

  • Secret documents: Government records, censuses, financial documents.

  • Other documents: Financial summaries, wills, and even shopping lists can serve as sources.

1.1H - Digital Sources

1. Digital Sources (DS)

• Definition & Examples:

  • Includes blogs, vlogs, and social media (e.g., Instagram, Twitter).

  • Considered secondary data and can reflect social trends.

• Strengths:

  • Accessibility: Available at low cost, and easily accessed globally (practical advantage)

  • Comparability: This can be used to compare information across different regions

  • Insight: Provides detailed qualitative data

• Limitations:

  • Reliability Issues: This may contain misleading or biased information.

  • Validity Concerns: Important context (author’s background, intentions) may be missing 

  • Government Control: In some countries, digital access is restricted

1.1I - Media Content

1. General Points

• Media content includes traditional media like newspapers, magazines, TV, and films.

• It is widely consumed and influences societal views and attitudes.

• Feminist sociologists study media representations, particularly how gender roles are reinforced.

2. Uses of Media Content

• Source of specific information: Can be used in literature reviews for research.

• Sociologists may use TV documentaries along with written sources.

• ! Caution is required due to bias and selectivity in media content.

3. Reality vs. Imagination

• Novels and films explore themes of interest but may not always reflect reality.

• Media can bring experiences to life, but it is hard to distinguish fiction from reality.

4. Strengths

• Readily available and cost-effective source of information (practical advantage)

• Good starting point for further research.

• Can be analyzed quantitatively (e.g., counting occurrences of certain themes)

• Reliable and repeatable for analysis

5. Limitations

• Validity issues – Hard to verify the truthfulness of media content.

• Subjective bias – Important to consider who created it and why.

• Quantitative analysis may lack depth – Counting occurrences do not always capture deeper meanings - ‘skims the surface’

1.1J - Analysis, Interpretation, and Evaluation of Data from Qualitative to Quantitative Sources

1. Interpreting and Evaluating Evidence from Qualitative Sources

• Key Questions for Researchers:

1. Who produced the source? (Consider point of view, class bias, literacy)

2. Why was it produced? (Purpose of publication)

3. Author’s position (Were they in power? A direct witness?)

4. Bias or subjectivity?

5. Representative of common views at the time?

6. Are there supporting or contradicting sources?

7. Intended interpretation by the author?

2. Summaries of Studies (Secondary Sources)

• A secondary source summarizes research findings.

• Commonly presented as research articles.

• Research articles typically start with a summary of existing knowledge.

3. Literature Review (LR)

• Overview of previous research on a topic.

• Helpful but not always comprehensive.

• Must be checked against primary sources for accuracy.

4. Interpreting and Evaluating Evidence from Quantitative Sources

• Researchers must decide the best format to present data.

• Data should be accessible and easy to understand (practical considerations)

• Formats include tables, charts, and graphs (visual data)

5. Key Skills for Sociology Students

• Ability to interpret, extract, and present data.

• Construct different ways of visualizing data.

6. Overall

• Sociologists must evaluate qualitative and quantitative sources.

• Common secondary sources include research articles and literature reviews

1.1M Qualitative and Quantitative Primary Research Methods

1. General Points

• Primary research is firsthand data collection by a researcher.

• Can be quantitative (numerical data) or qualitative (descriptive data).

• Methods include:

  • Surveys (structured interviews, questionnaires)

  • Interviews (structured, unstructured, group)

  • Observations:

    • Covert: Researcher hides their identity.

    • Overt: Researcher discloses identity.

2. Surveys

• Typically conducted on a large scale.

• Preferred by positivists (favour quantitative data).

• Interpretivists prefer qualitative methods like:

  • Semi-structured interviews

  • Unstructured interviews

  • Some types of observations

3. Questionnaires

• Also called self-completion questionnaires.

• Respondents complete them without researcher guidance.

• Common distribution methods:

  • By post (traditional)

  • Online (e.g., SurveyMonkey)

  • Handed out in person (e.g., by teachers)

4. Response Rates & Representativeness

• Low response rates (<50%) can impact representativeness.

• Respondents may not be representative of the target population

• Unanswered or misunderstood questions affect the validity

5. Improving Response Rates

• Sending reminder letters.

• Keeping questionnaires short and clear.

• Giving clear instructions.

• Personalizing letters.

• Offering incentives (money, prizes).

6. Guidelines for Creating Questionnaires

• Keep them short and easy to follow.

• Use simple and clear language.

• Avoid leading or persuasive questions.

• Avoid complex vocabulary.

• Include both closed and meaningful open-ended questions

• Ask for personal information at the end

7. Strengths of Questionnaires

• Can be used with large samples, aiding generalization.

• Allow participation from distant respondents (practical advantage).

• The researcher's absence prevents influence on answers (supports validity, lowers researcher imposition)

• Respondents can complete it at their convenience.

8. Limitations of Questionnaires

• Low response rates affect representativeness.

• Misunderstood questions lower validity.

• The researcher cannot verify if the respondent personally completed the questionnaire.

• Some questions may be left unanswered.

1.1P - Types of Questions

1. Importance of Choosing the Right Type of Question

• Helps in selecting the correct research method.

• The type of question determines the type of data collected

• Facilitates easier data analysis.

2. Main Types of Questions

• Open Questions (Qualitative Data)

  • Allows respondents to explain and expand on answers.

  • Often start with "Why," "Give reasons for your answer," or "Explain how."

  • Common in semi-structured and unstructured interviews.

  • Rare in questionnaires as respondents are less likely to provide long answers.

• Closed Questions (Quantitative Data)

  • Multiple Choice Questions (MCQs)

    • Contains a stem (opening statement) followed by several alternative answers.

    • One correct answer (the key).

    • Used in education and assessments.

• Scaled Questions

  • Have a range of possible answers (e.g., strongly agree → strongly disagree).

  • Debate over using an odd or even number of response options:

    • Odd number: People tend to pick the middle option.

    • Even number: Forces respondents to make a decision.

    • Helps in measuring opinions/preferences but may lead to forced choices

1.1Q - Practical and Theoretical Issues Affecting Research

1. Practical & Theoretical Issues in Research 

• PET Formula (Practical, Ethical, Theoretical issues)

• Practical: Time, money, resources, response rates, transcription difficulties.

• Ethical: Anonymity, confidentiality, informed consent, risk, harm.

• Theoretical: Positivist vs. Interpretivist approaches, validity, reliability, generalizability.

Practical Issues

• Access to Sample: Some populations (e.g., learners, criminals) are difficult to reach

• Response Rates: Low response rates impact generalizability.

Funding & Costs

Funding is easier for quantitative research (trends, correlations).

Qualitative research is harder to fund (small-scale samples).

Universities may fund research but require justification.

Time Considerations

Qualitative research: More time-consuming (e.g., participant observation takes years).

Quantitative research: Faster (e.g., surveys).

Longitudinal studies: Require revisiting samples over time, making funding difficult.

Theoretical Issues

Positivists: Favor structured methods (e.g., surveys) to prove/disprove hypotheses.

Interpretivists: Prefer unstructured methods (e.g., interviews) to explore meanings.

Researcher Values: Influence research topics (e.g., Marxists focus on class issues, feminists on gender).

1.1R - Ethical Issues Affecting Research

1. General Points

• Sociological research involves people, so ethical considerations are crucial.

• Ethical issues affect the welfare of both respondents and researchers.

• Decisions on ethics involve determining right and wrong.

2. Main Ethical Guidelines:

• Participants must give informed consent.

• They must not be harmed (physically or psychologically).

• Researchers must respect privacy and confidentiality.

• Deception should be avoided unless necessary.

3. Codes of Conduct:

• Established by professional associations to guide ethical research.

• Aim to protect individuals and organizations involved.

• Provide guidance rather than strict rules.

4. Anonymity & Confidentiality:

• Anonymity: Participants' names and identifiable information should not appear in research data.

• Confidentiality: Ensuring individual responses cannot be linked to participants in published findings.

• Difference: Some studies (e.g., Census) collect personal details but publish only statistical data.

5. Informed Consent:

• Participants must agree to take part with full awareness of the research purpose.

• Includes explaining research objectives, findings availability, and potential uses.

6. Participants' Rights:

• They can refuse participation or skip questions.

• Researchers must not coerce participants.

7. Challenges in Informed Consent:

• Not always possible, especially in large-scale or covert research (e.g., participant observation).

• Debate exists on how much information is necessary for participants.

8. Privacy & Confidentiality:

• Researchers must respect participant privacy even if consent is given.

• Participants can refuse to answer sensitive questions.

9. Deception in Research:

• Sometimes used when revealing true purposes may affect results.

• Can include misleading participants or giving incomplete information.