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Lecture

SY 280 Sept 21.doc

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Department
Sociology
Course
SY280
Professor
Linda Quirke
Semester
Fall

Description
September 14, 2010 • Positivist Epistemology o August Comte  Religious beliefs replaced by science and objectivity  In the past god’s will= what society wants  Wanted society to be explained logically and rationally  Increase the status of Soc by making it more like science  Empiricism • Objective and value free o Tenants of Postivism  Science approach  Research= testing theories laws of social science  Empirical observation not influences by old theories o Positivism Under Attack  Pejorative term, superficial data collection  Criticized by Fems, Marxist and Interpretivists  Doesn’t acknowledge unequal in society, race, class, gender • Interpretivist Epistemology o Critical of positivism o Cant be scientific with the subject matter o o Verstehen: interpretive understanding of social action o Look at the world through subjects eyes • Empiricism o Philosophical approach o Only knowledge from senses acceptable o Rigorous scientific testing o Accumulate facts = data o Dismiss research that doesn’t connect to theory • Theory and Research (Marx and Morton) o Theory  Explanation of observed regularities  Guides the collection of data and analysis  Grand theory • Marx, Feminism • Don’t suggest how to collect data, • Don’t know how to test  Middle range • Durkheim on suicide • Deduction more scientific o most common approach o in hypothesis concepts to be translated into researchable entities o Theory Observations + Findings o Theory data o Explicit hypothesis to confirm or object o Quantitative o Authority of knowledge= sociological community o Scientific o Traditional • Induction o Observations and Findings Theory o Data theory o Generalize o Qualitative research, o grounded theory  making theory from qualitative data o Wont narrow ideas o Authority of knowledge= respondents and society • Process of Deduction o Theory o Hypothesis o Data Collection o Findsings o Confirm or reject Hypothesis o Revision (restart @ b) SY 280 September 21, 2010 • Induction o No attempt to follow steps o Generalized inferences from the observations o Grounded theory o Qualitative approach • Problems o Looking at things that match the theory o Ignore what doesn’t fit • Scientific Research Process o Problem formation  What we want to study o Review of past studies o Theory  Process of making sense of the world around you, becomes hypothesis  Concepts • Abstract, often unmeasurable categories • Describe social phenomena • Love, violence, racism, social category • Very broad  Variables • Concrete and measurable • Varies across units of analysis  Independent and dependent variables  Hypotheses • Statements you make about how the world works • Statements about indi and depen vari  Rationales o Methods  Data collection strategy  Population and sample  Variable measurement  Statistics o Results and Discussion  Long term effects o Conclusion • EX 1 o Problems?  Grades vs class attendance o Past Studies o Theory  Concepts • Grades • Class attendance  Variables • Inde • Depen  Hypothesis • Those who go to class get higher grades  Rationale • If you come to class you get more info • Ppl who come to class do because they aren’t doing well  Methods • Data collection strategy o Survey • Pop o Students at certain levels, school, etc • Sample Research Design • Main purpose of research o Exploration  Satisfy researchers curiosity, new understanding  Test feasibility of undertaking extensive study  Develop methods for later use  Smaller  How to start in a new area of study o Description  Observe, describe  Census, describe characteristics o Explanation  Why??  Casual relationship between variables • Research Strategies o Quantitative  Measure social variables  Lots of surveys and experiments  Numbers and stats  Deducting testing  Positivist epistemology  Objectivist view of reality • Reality is external to social actors • Things exist outside of the mind of the subjects being studied o Qualitative  Lots of interviews and ethnography  Data= words, texts and stories  Inductive approach  Interpretivist epistemology • Understand subjective meaning of world of the subjects • Personal opinion • Understand the point of view of the subect o Broad classification of methods of social research o Differ  In general orientation to social research  Epistemological foundation  Different views of how to do research • Units of Analysis o Person/ thing you collect data from o Individuals o Groups o Orgs o Countries o Social artifacts o Faulty reasoning about units of analysis  Ecological fallacy • Assumption that something learned says something about individs in that unit • Generalize based on group data  Reductionism • o What we examine to make description of all units • Time Dimension (video from last day) o Cross-sectional o Longitudinal • Experimental Design: The Classic Experiment September 23, 2010 • Units of Analysis o Individs  Most common in social science o Groups o Orgs o Countries o Social artifact  News paper article  Work of art  Product of social beings or their behaviour o Faulty resoning about units od analysis  Ecological Fallacy • Assuming that findings about group reflects on the individuals in that group • High crime rate in city = ppl in big cities more likely to commit crimes • Can only make conclusions at the group level  Reductionism • Try to boil down complex social patterns into narrow concepts • Time Dimension o Cross sectional  Observations made at one point in time  No follow up  2011 Census  Exit poll after election  Opinion poll  Take one slice and look at it o Longitudinal (better, more data)  Trend Study • Different people are asked the same question at different points in time • Most common • See a pattern over time to detect shifts and changes of opinions, events, etc • Long term changes in the society  Cohort Study • Group of individuals who are linked have experienced same significant life event within a given period • Tragedy • Common thing that everyone has gone through in the group • Baby boomers • Ask people at certain time, then wait and ask again 5, 10, 20 years later • What has happened in the years between ? • Less expensive • Harder because of mortality, trying to find the same people • Identify the cohort effect  Longitudinal/ Panel studies • Same individuals over time • Show volatility in each respondents intentions and opinions • Follow ups • Movie o 7 year olds asked about social class, love, work, race, and life etc in 1964, follow them over time o Tried to predict what they would be like when they are older • + possible exam question o In depth stuff o Ask more questions o Develop relationship with participants o More comfortable with the interviewer • - o Narrow view of the world o Hard to keep in contact o Ethics (children) o May “act” because they are on tv o Death o Expensive o Difficult to generalize, not rep the population o People drop out o Skewed sample • Experimental Design (not used very much, unpractical) o Purpose  Est causal relationship between ind var and dep var  Does one thing cause another??? o Random assignment of subject to experimental and control groups o Ind var manipulated all others held constant o Classic Experiment  Lab experiment • Cover story o Lie to them, plausible o Sets stage o Don’t let them know what is really going on o Include in the write up what lie you told to get ppl to participate o What they are told may affect behaviour, say as little as possible o Deception  Ethical issues  Only way to get most natural behaviour  Don’t know if you are experimental or control group o Informed consent • Random assignment o Experimental and control group o Must be random o Inadequate assignment o Intact classes o Self selection o Systematic differences • Manipulation of IV o Groups: exposed to various levels of IV o What event corresponds to theoretical IV  Make ppl in the study do something o How to present level of IV:  Produce powerful, maximum effect  Enough to produce a change, not too little or too much, effective as possible  True impact seldom recreated • Identical treatment of groups o Manipulation of IV must be the ONLY difference between the 2 groups o Double Blind  Experimentors don’t know what group participants are part of  Reduce bias • measure DV o purpose  manipulate IV  measure the change caused o Dilemma  Tip off participants, influence response  People may try to exaggerate to help experiment  Limitation • Types of questions o Lack of suitability • Generalizability of findings o artificial environment o not how people would normally act o sampling: non probability  only get those who want to participate :students $$$ o triangulation  use of more than one method or source of data in a study, findings cross checked September 28, 2010 • Quantitative Research o Criticisms of quantitative research MIDTERM • TV and violence example possible midterm question!!!! o Or describe the pros and cons o Chapter 1-3 and 8 • Quantitative Researchers: Mian Preoccupations o Measurements  Quantified  Compare measures  Changes in variable over time o Causality  Something makes another happen  What explains social phenomena o Generalization  Can you generalize beyond your population  Broad terms  Not just true for the sample population  Apply what you found beyond your pop  Need a good representative sample o Replication  Replicate studies that are already out there  Detailed procedure of that study • Criticisms o Natural world vs social  Doesn’t tap into how people actually behave  Doesn’t distinguish between natural world ans social phenomena  Doesn’t tap into ppls interpretations of what they actually do  Ppls subjective view of self  Self reporting o Precision and accuracy  Artificial sense of precision  Presume connection between concept and measure  May not understand the meaning of a question o Lacks validity  Gap between actual behaviour and stated behaviour  Ppl lie o Static view  Ignores human interpretation  Don’t get a complete view of the world • Formulating Research Questions o Considering factors relevant to research topic or question  Don’t want to choose something that everyone already knows  Add new information to the area o Choosing factors  Not been investigated before  Contribute to understanding of topics  Interests  Leads to new research questions • Testing Hypothesis o Formal statement regarding the relationship between variable o Tested directly o Posing questions in a testable form o Types  Null H 0 • Represents NO relationship between variables o No difference between groups A and B o Any relationship is just chance o H0: ua=ub o U thing= theoretical average of pop  Ua average for group A  Ub average for group B o Starting point o Benchmark  Research H 1 2 • Definite statement of relationship between two variables or difference between groups • H1: Xa =/ Xb (not equal) • Posits relationship between variable not equality  H1= research hypothesis • Xa= average score for sample group A • Xb • Example o Do hot profs give higher or lower grades  Rationals for both sides o Group A: Attractive Profs o Group B: Unattractive Profs o Represents NO relationship, no difference  No difference between groups A and B  Groups are the same ua= ub o Assumes any difference is due to chance o Always start with the null hypothesis o Definite statement of relationship between two variable, difference between groups not equality o H1:  Xa Grades given by A attractive profs  Doesn’t equal Xb average for group B unattractive profs  H1 = research hypothesis • Concepts o General abstract unmeasurable categories o Describing social phenomena that are difficult to meausure o When you see something happening and don’t know how to label it  See social class  Violence  Intelligence  Health  Discrimination o Hand out page • Variables o Class of outcomes that can take on more than one value o Trait varies across units of analysis o Something that varies o Subunits= attributes o Hair colour ( blonde, brown..) o Height ( different heights) o Education • Independent Variables o Manipulated or changed o Variable whore variation is independent of other variables in the study o Produces variation in the dependent variable o Doesn’t dependent on any variables to do something • Dependent Variable o Examined as the outcome of an experiment or research project o May depend on experimental treatment or on what the researcher changes or manipulates o Variation depends on variation in other variables ( ex. the independent variable) • Ex o Does education make people more prejudiced or more tolerant ?  Variables • Education level ( less than hs, uni) • Prejudice (pre or un) September 30, 2010 Measurement: Validity and Reliability • Measurement o Levels of measurement  Nominal • Variables: labels or names • Hair colour • Religion • All equal, cant rank • Nationality  Ordinal • Variables with attributes we can logically rank • Education  Interval • Distance separating attributes of variables has meaning • IQ  Ratio • Variable has a zero point • Income • Validity MIDTERM o Accuracy of the measure o Measures what it is supposed to measure o Does an indicator accurately measure what it is intended to measure  Question on survey  Scale o Extent to which an empirical measure adequately reflects the real meaning of the concept  Something that can be scored  Logic of validation • If we have been successful in measuring some variable then our measures should result in some logical way to other variables • If results contradict prediction, must look back o Ex  Want to look at your questions and responses, and say with confidence: I know that these measure job satisfaction • Measure with low validity • Want the questions to accurately measure job satisfaction • Use independent variables that will have a strong impact on the dependent variables • If scale doesn’t measure what is was meant to measure it is not accurate not valid o Internal  Intersubjective, expert based validity • Based on internal logic of the scale  Look at the items in a scale- ask do the items make sense  Face • On the face of it do these items in this scale make sense • Ex: friendly co workers: the extent to which informal social bonds bind workers to each other o Extent to which workers feel an intrinsic to their job, whether the job is important to them o Makes sense that if there are people on the job that are friendly to workers, workers should feel more bound and tied to their workplace • Scale o Coworkers are friendly o Help me on the job o Are competent o Are personally interested in me • Are these valid measures of ties to the workplace o Competent:can be competent and friendly o Goes back to definition of your variable to find face validity of a variable, keep checking back  Content • The degree to which indicators cover all of the generally accepted meanings of a variable • Do items on scale contain all the pertinent aspects o Are the items in the scale covering all generally accepted meanings of what you are interested in • Ex: drinking problems= the extent to which drinking interferes with someone’s daily life o Miss work due to drinking o Alcohol in the morning o Worry about drinking o Drink on the job o All these q’s are good • Does it have high face validity? o Yes • No does not cover 2 areas where drinking problems manifest themselves: family and friends o 2 really important contexts dealing with drinking problems which are not covered in the scales here • External o Less subjective than internal validity  More objective o Two types below o Criterion  Valid • Enables researcher to predict some other thing • Predict another variable  Dealing with a second variable (ex driving skill) that occurs in the future • Written driving test score number of car accidents  Predict which drivers are going to be safe versus dangerous drivers?  Can it predict the outcome?? o Construct  Ability of a scale to predict some other variable that is theoretically related to the scale  link between scale and other variable est by formal theory  ex: drinking problems spousal abuse • scale shows ppl who drink a lot more likely to abuse their spouses • Reliability o First is measure accurate, valid?? o Is measure consistent o Particular technique applied repeatedly to the same object yields that same results every time o If it gives consistent results then it is reliable  Reliability does not ensure accuracy o Over time  Extent to which a scale produces the same results over time • Ex, test retest reliability  Person who responds to score items will come up with the same results each time  Intervening events that can confound your ability to document the reliability of a scale over time o Internal Consistency  Consistency of scores a person had across items in a scale  Want each person who has responded to score similarly in all measures  Consistency in scoring across items in a scale for each individual  Problem:  Ex • Satisfied with job, take same job, recommend job • Person 1 answers all low • Person 2 answers all high • Person 3 low, low high o Not internally consistent o Inter-coder Reliability  Extent to which different people code or interpret a response in the same way  If you have 3 people coding an interview will they all interpret responses the same way  Needed for qualitative data  When collecting lots of data might hire coders to help analyze  Oct 5, 2010 • Inter-docer Reliability o Extent to which different people code or interpret a response in the same way, needs to be reliable o If you have 3 people coding an interview will they all interpret responses the same way o When collecting lots of data, might hire coders to help analyze  Can lead to lots of problems o Want everyone to be on the same page o Testing  Have someone else look at 10% of the stuff and rate o Validity and Reliabillity (look at images in notebook)  The research methods do not hit the heart of the research aim and repeated attempts are unfocused  Methods don’t hit aim, attempts get almost the same (but wring)) results  Methods hit aim but attempts are scattered  Methods hit hearts and attempts hit the heart as well • Tension between Validity and Reliability o Reducing validity  Reliable operational definitions and measurements seems to rob concepts of their richness  Qualitative and idiographic methods get more valid results o Reducing reliability  More variations and richness we allow for a concept, more opportunity for disagreement on how it applies to a particular situation. Thus reducing reliability  Quantitative, nomothetic structured techniques more relaibel Midterm Review • Research Process o Positivism and Interpretivism  Scientific social laws, testing theories, verstehen (Weber, I)  Identify both of them o Empiricism  Sensory experiences  Positivism o Theory and Research  Grand theories, middle range theories o Approaches to Research  Deduction • Scientific research method • Often quantitative • Friend with positivism • Theory then observations,  Induction • Observations/ data collection then theory creation, grounded theory often qualitative • Scientific Research Process o 1-6 • Units of analysis o Ecological fallacy o Social artifact o Etc • Time Dimension o Cross sectional o Longitudinal (trend, cohort, panel) • Experiments o Purpose, cover story, random assignment, manipulate IV, identical treatment of groups, measuring DV, limitations o Artificial • Quantitative Research o Preoccupations, criticisms • Hypotheses and Variables o Formulating research questions o Testing hypothesis  Null hypothesis  Research hypothesis o Concepts o Variables  I  D • Measurement: Validity and Reliability o Nominal, ordinal, interval, ratio o Validity  Does indicator measure what its supposed to measure, reflects real meaning on concept  Internal • Face and content • Items make sense, cover all meanings  External • Criterion o Predicts triangulates • Construct o Predicts based on theory  Reliability • Over time • Internal consistency • Inter coder reliability • Interative p 6 o The collection of data, go back to theory more data etc etc • Verstehen p8 o Empathetic understanding Oct 12, 2010 • Conceptualization and Operationalization o Conceptualization  Refinement and specification of abstract concepts  Take something big make it smaller, concrete, specific  Process of coming to an agreement about what terms mean  Specifying what we mean when using terms in research  Ex. Recipe  Specific agreed upon meaning of a concept to be used in research  Concepts • Ex Homophobia, compassion • What we produce through conceptualization • Something we create • Can be a construct  What social scientists measure • Direct observables o Things you see when you look at someone o Hair colour, gender • Indirect observable o Survey, questionnaire, interview o Account given through a different tool • Constructs o Artificial measure of intelligence (IQ) o cant observe directly, or indirectly o theoretical creation based on observations, o ex IQ test o IQ created or constructed measure of intelligence  Indicator • Sign or presence of the concept we are studying • Yes/ no questions • Tells us if someone is acting in a certain way • Ex. Shows homophobia, alcoholism etc • Statement or question used to measure a variable • Ex. Job satisfaction o Each q indicates yes or no • Educational aspiration o Bad indicator ex o How much edu do you think men and women should receive  Double barreled  Dimension • Groupings of indicators • Feelings of homophobia • Actions of homophobia • Fit together with the theme of the variable  Interchangeability of Indicators • If several indicators all represent the same concept then all would behave the same way, measure the concept in the same way • Doesn’t matter if you add new ones or get rid of some o Operationalization  Development of specific research procedures (operations) that will result in empirical observation representing concepts in the real world  Start with big concept, end with little definition  Recognize the steps for the test  Identify  Operationalization cooices • Range of variation o Way of combining attributes into larger categories o Include every single possible answer o Include 0 o No one should be left out o Other box in survey o Ex. Political beliefs • Precision o Ex.Don’t need to know months just years for age o Children you want months  Attribute • Characteristic or quality of something o Female or male • Mutually exclusive • age 20-25, 25-30, 30-35 not mutually exclusive  Variable • Logical set of attributes o Gender • Young, pretty young, pretty old, old  Defining variables • Definitions o Conceptual  Broad definition, dictionary o Nominal  Arbitrary definition assigned to a term without any claim that the definition represents a real entity  Working definition, before operational o Operational  Final  The recipe  Exactly how to measure the variable  Exactly what we will observe and how to measure  Definitions in: • Descriptive o Very important o How do you define being unemployed • Explanatory o Less problematic o  EX What is a Drop Put • Conceptual o Uneducated person • Nominal o Someone who hasn’t finished high school or university • Operational o voluntary withdrawal from university prior completion of degree requirements  EX hotness • Conceptual o Attractive, good looking • Nominal o Physically attractive characteristics • Operational o Chili pepper on ratemyprofessor.com  EX Princess • Conceptual o • Nominal o • Operational o o Measurement steps  Conceptualization nominal definitionoperational definition measurements in the real world October 19, 2010 • Hypotheses o Statement of relationship between variables  Null hypothesis • No relationship between IV and DV  Research hypothesis • IV increases DV will increase/ decrease o Or can be statements of differences between groups  Null hypothesis • No difference between groups’ average sores  Research hypothesis • Different average scores between groups • Relationships between variables o 3 was to state a hypothesis  Predict either • No relationship • Or relationship, correlation: either positive or negative o No relationship  Null hypothesis assumes o Positive  Positive relationship between an independent and dependent variable , can say that these variable co-vary • As IV increase DV increases etc
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