research methods Flashcards
macro
- sense of social structure
- objective
- large scale
- positivist
micro
- indviduals
- meanings of interactions
- subjective
- interpretivist
primary data
generated first hand
secondary data
using data which already exists
quantitative
methods which generate numerical information
qualitative
methods which generate in-depth data
positivism
- identify underlying causes
- quantitative data
- cause and effect
interpretivism
- qualitative data
- understanding
- how people give meaning to the social world
valid
- true measurement of social reality
- interpretivist
- depth and detail
reliable
- trustworthy and replicable
- contradicts with validity
- quantitive, consistency of data
generalisable
- make claims about target population based on sample
- depends on representative
- size of sample
representative
- typical/reflects the target population
- positivists
- typical characteristics
sampling frame
list of members of the sample population to be studied and their contacts
random sampling
simple, systematic, stratified
non random sampling
opportunity, quota, snowball
simple random
randomly selecting people from a list of names
+/- simple random
+ everyone has an equal chance
- doesn’t guarantee the outcome the researcher wants (disproportionate)
systematic random
numbering participants and picking them at set intervals
+/- systematic random
+ not biased
- not representative
stratified random
dividing the population into smaller groups
+/- stratified random
+ more specific to age and gender
- could be biased
quota
selects people to fit into certain categories
+/- quota
+ can fit target population
- biased as researcher looks for them
snowball
asking someone who fits the criteria if they know other people
ethical questions
- unpaid
- no harm
- confidently
- informed consent
- no deception
- anonymity
gatekeepers
a person who keeps the information
advantages of longitudinal studies
- spot patterns and trends over time
- see cause and effect relationships
- used by positivists and intrepretivists
- reliable as its repeated
- large scale with a large sample
disadvantages of longitudinal studies
- people drop out over time
- high cost in time and money
- research methods can be problematic
- the research can change peoples thinking
pilot studies
test run of the research
- used before questionnaires and interviews
advantages of pilot studies
- saves wasting time
- improves questions
- trains the researcher
- overview of time and cost
disadvantage of pilot studies
- expensive
- delays study
- contaminate the research
- sends a bad message
social surveys
- questionnaires and structured interviews
- produces standardised data
types of questions
- open
- closed
- graded
advantages of questionnaires
- collect information from a lot of people
- can use all types of questions
- identifies correlations
- representative and reliable
disadvantages of questionnaires
- producing good questions is problematic
- closed and graded limit response
- may lack validity
questionnaires
standardised list of pre set questions asked by the researcher
ways to interview
face to face, phone, internet
3 types of interview
structured, instructed, semi-structured
advantages of structured interview
- standardised data
- easy to compare respondents
- easy to replicate
- large numbers
- quick and cheap
disadvantages of structured interview
- lack validity
- lack depth
- lack flexibility
- the same question could be interpreted differently
advantages of unstructured interview
- validity and depth
- better understanding respondents
- leads to new ideas
- reduced interviewer effect
disadvantages of unstructured interview
- less standardised
- less reliable
- more time and money
- avoid cherry picking information to fit hypothesis
overt non participant observation
openly observing peoples behaviour with consent
covert non participant observation
observing people who are unaware they’re being observed
overt participant observation
being involved with the participant while observing them with consent
covert participant observation
being involved with the participant but not telling them you’re observing them
focus group advantages
- researcher understands why people have certain opinions
- study group interactions
- the group will prioritise issues they find more important
focus group disadvantages
- researcher has less control
- time consuming and expensive
- analysing the material is difficult
+/- overt non participant
+ its honest
+ positive
- Hawthorne effect
- unnatural
+/- covert non participant
+ less likely to change behaviour
+ less time consuming
- explanations are limited
- unethical
+/- overt participant
+ easier to record observation
+ doesn’t have to worry about being discovered
- may not behave naturally
- researcher may not be accepted
+/- covert participant
+ more valid
+ gain understanding from new pov
- getting accepted and exit is hard
- time consuming and expensive
ethnography
data gathered on direct observations of a particular society, focusing on beliefs, language, practices and social differences
advantages of ethnography
- detailed and valid
- high in ecological validity
- can combine different research methods
- provides a naturalistic descriptive account
disadvantages of ethnography
- lacks representativeness and generalisability
- can’t be replicated so no reliability
- time consuming
- ethical issues
- objectivity is problematic
official statistics
numerical data collected by the government, gathered by surveys carried out by state agencies (e.g the ONS)
unofficial statistics
quantative data that is collected by non-government sources such as employers, professionals, political parties and charities
advantages of statistics
- easy and cheap to access
- they’re up to date
- positivist as collected in a standardised, scientific way
- gathered from large representative samples
- often form a basis of hypotheses for research
disadvantages of statistics
- definitions used by organisations may differ from sociologists
- statistics can be changed by the government for political advantage
- socially constructed so could be bias
- tell us very little about human behaviour that underpins them
hard statistics
are thought to be reliable and valid as there’s a legal requirement for them and they’re very specific (divorce, birth and death rates)
soft statistics
are less reliable as they cover areas that are difficult to define accurately (crime stats by the police0
police crime statistics problems
- so many crimes aren’t reported
- police don’t record all crimes or take them seriously
- ‘the dark figure’ is the unknown number of crimes
content analysis
- analysis of the media or documents
- can be quantative (numbers of articles)
- can be qualitative (themes)
criteria for document to be used
- authentic = is it genuine?
- credibility = is it accurate?
- representative = is it a complete account the situation?
- meaning = can the researcher understand the document?
3 types of content analysis
- formal - classifies content in an objective manner but ignores meanings
- thematic - looks for motives and ideologies but interpretations may not be correct
- textual - how the text encourages a certain reading but it may not
advantages of content analysis
- cheap and easy to access, so it’s up to date
- sometimes it’s the only way to research a topic
- can spot patterns and trends overtime and compare them
- positivist approach is reliable as it can be repeated
- large studies are representative and generalisable
disadvantages of content analysis
- must accept definitions of concepts
- the data may be bias and inaccurate
- personal documents are subjective
- lacks validity
- researchers subjective could effect the data
mixed methods
the combination of multiple methods of data collection
- primary and secondary
- qualitative and quantative
triangulation
multiple research methods are used to cross check the findings for validity and consistency
methodological pluralism
multiple research methods are used to build a fuller picture, usually combining quantative and qualitative
advantages of mixed methods
- fuller picture and cross checking
- wider range of data
- strengths of one method can compensate for the weakness of another
- could combine positivism and interpretivism
- combine primary and secondary data
- adds benefits to the key concepts
disadvantages of mixed methods
- results may not be consistent so reduces validity
- time consuming
- too much data can be costly
- too complicated
- greater skills needed by the researcher
- can be overkill
- puts contrasting approaches together which might not work
- negative effects on the key concepts
