Sociology

Durkheim’s Sociological Theory on Suicide

Egoistic Suicide: suicide related to lack of integration.

Altruistic Suicide: suicide related to too much integration.

Anomic Suicide: suicide related to lack of social regulation (lack of rules, meaning and limits).

Fatalistic Suicide: suicide related to too much social regulation.

Anomie: occurs when big changes that alter our meaning, or our rules, and that give us limitless options with no clear direction or end point.

Men: age 65 have a likelihood of suicide.

Women the age of 45-54 have a likelihood of suicide (3 reasons): Done having kids, their children are going to college/leaving the house, the kids are all grown up.

Unhappiness Theory

Sociological Methods in Sociology and in Everyday Life: Using and Understanding Evidence and Statistics

Three ways we can deal with Statistics:

• Naïve. We see a number that fits our worldview & we accept it without asking important questions.

• Cynical. We see a number that challenges our worldview & we reject it (we say “numbers can say anything & we reject it but with the same lack of understanding that one naïvely accepts.

• Critical. One determines how a statistic was arrived at in terms of sample & measurement & assesses whether the sample was representative of & the measure was appropriate and assesses based on these whether or not it confirms or challenges one's worldview.

1. Who created the statistic, 2. Why did they create the statistic & 3. How was the statistic created?

Sources of Bad Statistics

1: Bad Guesses are the most primitive source of bad statistics.

• Activists, Policy makers, Reporters, & other advocates who hope to draw attention to a problem or issue will find there aren’t good records on the prevalence of a problem. These numbers often get repeated and take on a life of their own.

2: Deceptive Definitions & Misleading Measures.

• Advocates for an issue will often use an example or scenario to describe a problem without clearly defining or explaining the boundaries used to define or count the problem.

• Ex: 500,000 missing children? The claim of 500,000 missing children should have made numerous people wonder why the same kids aren’t on milk cartons in ten different states. Wouldn’t there be 10,000 kids per state?

• Even if parental kidnapping is added to this, the numbers are still low.

• Common problem is that the public definition of the problem is an anecdote or example while the definition used to measure the prevalence of the problem is much broader.

  • Survey questions can also be misleading.

  • Push/Polls; they’ll call you pretending to convince you to vote in support for questions they made about someone or something.

  • Absolute Numbers vs Rates.

  • Can occur when people report on total numbers rather than rates per capita for different sized populations.

  • Have to look at rate per capita instead of the absolute numbers

3: Mangled or Transformed Statistics.

• Statistics where the original numbers started out okay but overtime it can get mangled or transformed so it is no longer what it was before.

Mutant Statistic: 1995 Article

• Types of Samples:

  • Convenience samples (or self selected) are not representative. Samples that are easy to gather except they skew the results.

  • Unrepresentative, non-random samples often have a selection bias that favors one type of person over another and thus the sample does not represent the population studied.

  • Self selected sample, where the sample is convenient because you’re not the one actually doing the work.

• 5 - Faulty Causation and Spurious Causation

  • Initial statistic might be good but the interpretation of the statistic could be flawed.

  • The number is generally okay but the issue comes in how the number is interpreted.

• Exs: murder rates -and- ice cream consumption (goes up in summer bc there’s more people outside; they’re doing other things in the summer)

• Exs: Gateway drugs (more addictive- implied that it’s more dangerous and might move onto other kinds of drugs. [85-90%] 100%--milk, it’s more accessible; water, opportunities: needles, at school, young- not so much a causal variable than a gateway)

• Good Sources

  • Good statistics are based on more than a guess.

  • Good statistics are based on a clear, reasonable definition and clear reasonable measures.

    • The definition should be clear about what is counted and what isn’t.

    • Should talk about how the count of the problem was arrived at.

  • Good statistics are not mangled or transformed (often good to check the original source where possible).

  • Good statistics are based on a random representative sample:

    • Based on a representative, random sample

    • Watch out for statistics based on non-random convenience samples

  • Consider other causes for a correlation. Correlation does not necessarily equal causation. Good statistics will often attempt to control for other variables or will consider factors that might affect the correlation.

• IF a statistic is given W/O information about definitions, measures or sampling it is wise to look into it.

• In general numbers are useful and help us to understand the nature of problems.

• Being able to understand the strengths and limitations of various definitions and samples can help us to become better statistical consumers.

Sociology of Success & Failure

• Success leads to confidence.

• Excellence does not apply to talent, it is the explanation.

• Hoop Dreams example

• Chambliss argues that we use talent before excellence.

• Talent isn’t always predicted ahead of time.

• Accomplished sports athletes (before & after)

  • Excellence does not result from quantitative changes in behavior.

  • Excellence does not result from talent.

  • Excellence is not the product of socially exceptional or deviant personalities, unique personality traits, or great confidence.

• Chambliss: The Mundanity of Excellence

  • Qualitative differentiation not quantitative increase.

  • Talent does not explain excellence.

  • Success is ordinary; Motivation is ordinary.

• In the pursuit of excellence, maintaining mundanity is the key psychological challenge.

• Factors other than talent explain athletic success more precisely—in swimming the best predictors of success are 1. Geographic location, 2. High family income, 3. Having a good coach etc.

• Talent isn’t a good predictor of success, it is an ex post facto measure we use after success has been achieved. There is no evidence for talent as a cause other than success itself.

• Someone who has done something big or other important things before, has an advantage.

• Gladwell: Outliers

  • Success is the product of hidden advantages, extraordinary opportunities and cultural legacies.

  • It makes a difference when and where we grew up.

• Davidai and Gilovich: The Headwinds/tailwinds asymmetry

  • Headwinds create challenges for us.

  • Tailwinds help us along.

  • We tend to recognize the barriers and headwinds we face, while we tend to not see the tailwinds that assist us.

• Success in Wealth

  • You had to be around then but be at the right age to take advantage of the opportunities. Neither too old or too young.

  • Born in another time or place and they probably wouldn’t be rich entrepreneur geniuses.

• Why Genius doesn’t explain success

  • Beyond a certain threshold of IQ 120…there appears to be no added advantage in life with extra intelligence beyond that point.

• Terman’s Termites

  • In 1921 Terman identified 1470 children with IQ’s between 140 and 200. Termites (people selected because of their high IQs)

  • Expectancy to be famous, and successful was low. —They tended to earn decent but not remarkable incomes and most were average and some were even failures.

  • In Fact: the termites were barely more successful than other groups and in fact the only two Nobel Laureates tested by Terman’s fieldworkers actually were Terman rejects.

• Both Gladwell and Chambliss say it’s about opportunity and practice more than talent.

  • Gladwell-it’s the quantity of practice.

    • Idea is that you need to put in the time and effort.

    • Arguing planes are more likely to crash for more experienced pilots because then there’s only one pilot.

• Chambliss-it’s about the quality of practice.

  • It’s about the mundanity of the amount of hours in the practice.

  • Mundanity skills and of excellence

    • Becomes part of the lifestyle

    • Learn how to ask people for money in order to get them to give more money. (Politicians- give some info about themselves, why you should give, have the courage)

• Plane Crashes: The Sociology of Failure

  • Failures are rarely caused by a single dramatic major malfunction but rather by several routine, minor things all going wrong in rapid succession.

  • Routine ordinary problems that just happen to culminate & accumulate to create a disaster. None of each problem by themselves are severe…but the combination is.

  • An accumulation of minor difficulties & seemingly trivial malfunctions.

• Typical plane crash—bad weather (not terrible), plane slightly behind schedule so pilot’s rushing a bit, pilot is tired, pilot & co-pilot haven’t flown together; so more of an issue with communication, up for more than 12 hours.

• Typically 7 consecutive small errors.

  • Mitigated Speech

  • Interact with the boss, parents, etc.

  • Importance of mitigated speech in relation to respected authority.

• Social Structure & Opportunity in Sport & Hoop Dreams