Sociolinguistic Variation Mid-Sem Flashcards
Stages of research planning
- Coming up with a basic idea
- Background reading
- Data collection and analysis
- Conclusion and introspection
Research questions should:
- Be informed by literature and evidence
- Define the design of your project (what kind of data, how to collect, how to analyse)
- Be answerable!
Interactional data
Recordings of language users in social interactions -> How people actually use
language in context
Attitudinal data
Surveys and/or interviews with language users -> What people think about language use,
describe how and why they use language
When recruiting participants for quantitative
data collection we need to consider:
- Population
- Sample
- Parameter
Experimental data
Controlled experiments where language users respond to stimuli -> How people
respond to stimuli and what processes are involved in their responses
Parameters
Parameters specify variables for analysis and
exclude others
Probability sampling
Everyone in the population has an equal chance
of being selected for the study
Four types of probability sampling
- Simple random: lottery-style selection
- Systematic: every X-numbered person on a list
- Stratified: organizing population into groups
who share certain characteristics then using
random sampling - Cluster: Sampling from smaller geographical
units
Non-probability sampling
Non-random selection – not equal opportunity for
selection
Four types of non-probability sampling
- Convenience
- Purposive
- Quota. Convenience sampling + quotas for different groups of participants
- Snowballing
Participant recruitment (2 ways)
- Self-selection
- Researcher selection
Selection bias types
- Self-selection bias
- Participant attrition
- Incorrect classification
- Cherry-picking
Quantitative data
Generally described as “numerical” data. Involves classifying features, counting them.
Qualitative Data
Non-numerical open-ended data. More inductive – making observations and then formulating
hypothesis/theory
Quantitative methods examples
- Surveys/questionnaires
- Experiments
- Corpus data
- Pre-existing statistical data
Qualitative data
- Interviews
- Focus groups
- Observations and ethnographic data
- Surveys/questionnaires - open ended questions
Types of interviews
- Structured
- Unstructured
- Semi-structured
Structured interview
Interviewer develops a set of
questions that will not change
throughout the interview process
Structured interview benefits + drawbacks
Benefits: Allows the interviewer
to focus very strongly on certain
topics – very easy comparison
across interviews
Drawbacks: No room for
flexibility means less depth
Unstructured interviews
no
pre-prepared questions, the
interviewer allows the interviewee to
guide the conversation ->
Interviewee has more power
Unstructured interviews benefits + drawbacks
Benefits: Relaxed interview
atmosphere
Drawbacks: data will often be
difficult to compare
Semi-structured interview
the interviewer has a set of
questions but will also be open to creating new questions in
reaction to interviewee’s responses
Semi-structured interview benefits + drawbacks
Benefits: Can compare different interviews, more
depth than structured interviews
Drawbacks: Interviewers have to decide on the spot if they’re
going to make adjustments to questions and how to do so
effectively
Types of questions
- Introductory questions
- Content questions: interviewee’s experiences with phenomena
- Probes: in reaction to information produced by the interviewee
- Closing questions
Interview phases
- Preparing the interview
- Beginning the interview
- Conducting the interview
- Closing the interview
Benefits of questionnaires
Good for eliciting attitudinal data (behaviours, beliefs, etc.).
Good for obtaining data from large number of respondents
More benefits of questionnaires:
- Economy of time
- Consistency assured
- Reliable comparisons
- Less interference from researcher (re: observer’s paradox)
Limitations of questionnaires
- Not great representativeness
- Self reporting can be inaccurate
- Often low rate of return
- Issues interpreting questions
Types of questions
- Likert scale
- Closed Questions
- Open-ended questions
Four types of open-ended questions
- Specific
- Clarification
- Sentence completion/elicitation questions
- Short answer
Questions content
- Facts
- Beliefs and attitudes
- Behaviours
Questionnaire format
- General introduction
- Specific instructions
- Questionnaire items (actual questions)
- Additional information
- Expression of gratitude
Corpus definition
A collection of data
Usually, corpus linguistics involves:
- Large collections of data
- Machine readable data
- Computer tools for analysis
Benefits of corpus linguistics
Computers can identify patterns across large
collections of texts more quickly than
humans
Corpus software allows
analysts to view every
example of a variant in a
text collection
Linguistic landscapes
Allows us to observe the roles of
different languages within a community
Three corpus techniques
Frequency counts, collocations, concordance analysis
Frequency
Involves counting the number of occurrences of
a particular word within a corpus/corpora
Uses of frequency
- Change over time
- Dialect variation
- “Standard” grammar/language use
- Spelling conventions
- Genre conventions
Concordance
Investigates which words
typically appear before and after
a word (probability)
Collocation
Looks at words that occur near the word under study
(referred to as the node). Typically, the collocation looks at a span 4:4 – or four
words to the left or right of the node
