Chapter 2
Concrete experience
touch, smell, taste, see, hear
Abstract Experience
The imaginative part of the mind that gives concrete experience meaning
Concepts
Terms for organizing concrete experience
Propositions
Statements that relate two or more concepts
Ideas about the social life
Unscientific Thinking: not good for sociology!
Bias
Casual Observation: we can be careless
Relying on Tradition: can be wrong
Relying on Authority: can also be wrong
Pseudoscience: claims that sound scientific, but really are not backed up by the standards of the scientific method
Takes advantage of selective observation and illogical reasoning, generating panic/hindering effective response by public agencies
Common errors in Inquiry
Overgeneralization
Treating an exception like a very plausible thing
Selective Observation
Only looking at the data you want to
Illogical Reasoning
Objectivity
“inter-subjective reliability
The degree of consistent observations from different people: a concensus
Insiders vs. Outsiders
Insiders: you have all the experience and know of the things that do and do not work
Outsider: you have different insights that may be new, but also cannot see the society more in-depth
Ethical Considerations
Voluntary Participation
Harm Reduction
Informed consent
Right to Privacy
Anonymity
Confidentiality
Authenticity
Debriefing
Ex: Indigenous people
Sick from residential schools, yet experimented on with supplement testing (vitamins)
Shows experiments should be led by the group being experimented on; include more research WITH and DONE BY Indigenous people
Positivism
Analyzing society with the idea that social realities exist independent of the observer and are “out there”, hence social realities are objective
Can measure all of society with quantitative data
deductive reasoning: starting with a general idea, then testing it
Speculation at first —> requires operationalization
Steps to Collecting Quantitative Data
Identify the theoretical idea of interest
Translate the abstract idea into a hypothesis through operationalization
Collect and analyze data
Accept or the reject the hypothesis
Hypothesis: testable form of a proposition
Concept —> variable
Proposition —> hypothesis
Quantitative Measures
Experiments: randomization and control/experimental groups
Want Validity and Reliability
Probability Sampling
Need Control variables —> no spuriousness!
Interpretivism
Social structures are subjective and we can only understand a society by understanding these subjective meanings which people put onto things (meanings and motives)
Inductive Reasoning: observe and draw out meanings, trends and themes
Qualitative Data Analysis, the steps of which are
Find research interest based on concrete experience
Collect evidence from one or more cases of the same type
Identify common patterns/themes
Use sociological concepts to interpret patterns and themes: stress that context matters
Qualitative Approaches
Purposive sampling + snowball sampling
Participant Observation, aka. Ethnomethodology (NOT ETHICAL!) → also usually denied access
Reactivity / Social Desirability Bias → both of which decrease over time without breaking ethical regulations
Key Informants: people who can guide the researcher with reliable information of culture, issues, activities, etc.
Unstructured / Semi structured interviews → a conversation
Stress Authenticity
Exploratory Research
Research that seeks to formulate theories rather than testing them
Focus Groups
Digital Sociology
Use of digital technology as a tool and a subject of research
Is nonreactive → does not affect those studied
Use of digital traces, which basically everyone has except the homeless
The sum of all digital traces = big data, requiring strong-ass computers
Data revealed:
On dating apps, more people go for people who are more desirable than themselves
Lower for old, educated women
Men mostly make first contact
Google Trends
More concern over daughter’s weight, more concern about son’s intelligence
More concern of son’s sexuality: “Is my son gay?” (but has not levelled off)
Advantages:
lowers social desirability bias
free, less sampling bias
Disadvantages:
Some people do not have wifi, hence not all are represented
“Dirty”: wrong information, trolls, duplicate data
AI is not real people
Breaches ethics: voluntary participation ;-;
Ultimately: subjectivity leads, objectivity follows (somebody makes a subjective idea, then people can agree and make it objective) (example: Gender revolution, somebody steps up and says its not equal, and objectivity follows)