Good morning,
The universal code sheets and code books have been posted.
Please code your assigned magazine covers and then email me your completed code sheets (jpowers@ithaca.edu).
I will summarize the data and return it to you promptly so that you can solve for chi-square and t-test.
In the meantime, use the posted finished report as a model for your own reports.
Our last day of class is Tuesday, but you may have as much time as you need to complete your final reports.
(But please try to complete the coding promptly so that others may finish their reports earlier if they so desire).
Sorry for the delay with this, by the way. I have no excuse except that I was sick all day Friday and Saturday and thought a message had been posted on my behalf. (Certainly sounds like an excuse, doesn't it? Lol).
Meanwhile, the Cleveland Indians' 14-game win streak ended yesterday on a controversial call at the plate. (I share because I know you care).
Let me know if you have any questions.
Jack
Sunday, July 3, 2016
Universal Code Sheet
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Coding Category:
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Numerical Value:
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1.
Year
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2.
Issue
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3.
#
of people on cover
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4.
Gender
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5.
Race
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6.
Age
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7.
Sexuality
of outfit
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8.
Smile
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9.
Darkness
of skin
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10.
Clothing
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11.
Skin
exposure
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12.
Color
of cover background
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13.
Sexuality
of pose
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Universal Code Book
Universal Codebook
1. Year of Magazine
2. Issue # of Magazine
3. Amount of people on
the cover
4. Gender of each person
on the cover
1.
Male
2.
Female
3.
Transgender
4.
Not able to be
determined
5. Race/Person of color
of each person on the cover
a.
1-White, 2-Black,
3-Hispanic, 4-Asian, 5-Other, 999
Person of color: This term will be defined
as anyone of non-Caucasian/white origin. This includes Asians, Blacks, Latinos,
etc. If the cover features a character that is not human, i.e. a cartoon, the
number 999 will be given to it, so as to exclude it from the actual data. The
category other is reserved for people
of mixed race or Arab descent (even though technically Middle Easterners are
classified by the US Census as being white).
6. Age
a.
1-Young
b.
2-Teenager
c.
3-Early adult
d.
4-Adult
e.
5-Middle Age
f.
6-Older Adult
g.
7-Old
7. Sexuality of outfit
a.
1-not sexual
b.
2-sort of sexual
c.
3-sexual
d.
4-very sexual
8. Smile
a.
1-no smile
b.
2-half smile
c.
3-smirk
d.
4-some teeth
e.
5-big smile
9. Darkness of Skin
1.
pale
2.
very light
3.
tan
4.
darker tan
5.
very dark
10. Clothing
1.
Costume
2.
Regular clothes
999. Other
11. Skin exposure
1.
little to no skin
exposure
2.
.
3.
.
4.
.
5.
extreme skin exposure
12. Color of cover background:
(1 = white; 2 = nonwhite)
White Space: This refers to the amount
of empty space on the magazine cover. For the purposes of this project, this
will just be quantified as having the color white as the background of the
cover. This is because an actual background color or place makes the cover look
more full and complete. A background color of just white makes it seem like
there is more empty space on the cover. If the cover is mostly white with a
little bit of other colors, it will be counted as white. However, if more than
25% of the cover is comprised of another color, then the cover should be
counted as nonwhite. This percentage will be determined from
observation/individual perception.
13. Sexuality of each person’s pose
a. 1 – 10 Scale (1 = Not
Sexual………..10 = Extremely Sexual)
Thursday, June 30, 2016
Please send hypotheses/code books
Good morning,
If you have not yet done so, please forward me your hypotheses and code books today.
(Put this at the top of your to-do list).
Once I have them, I'll compile/edit the code books into one document with a code sheet and then we can commence coding.
Thanks!
Jack
If you have not yet done so, please forward me your hypotheses and code books today.
(Put this at the top of your to-do list).
Once I have them, I'll compile/edit the code books into one document with a code sheet and then we can commence coding.
Thanks!
Jack
Monday, June 27, 2016
Sample Codebook and Final Project Overview
Ok, here's a sample codebook featuring some of the more common variables (feel free to use these variables and the accompanying info for your codebook)--
1. Year of Magazine:
2. Issue # of magazine:
3. Number of people on cover:
4. Name of each individual on cover, if applicable:
5. Gender of each person: (1 = male; 2 = female)
6. Race of each individual, if applicable:
(1- White; 2- Black/African-American; 3-Hispanic; 4-Asian; 5-Other)
7. Age:
1 - 0-15 year olds
2 - 16-25 year olds
3 - 26-35 year olds
4 - 36-50 year olds
5 - 50+ year olds
(Instead of using these categories, you may want to use general categories like "child," "young adult," "middle age," "older adult," "elderly"). The goal is for your categories to make sense for what it is your examining.
8. Seriousness of actor: (5-point scale where 1 = not at all serious and 5 = very serious).
9. Smile:
1. no smile
2. slight smile
3. closed mouth smile (smirk)
4. open mouth smile (little teeth)
5. big, bright smile (many teeth)
10. Wardrobe:
Regular Clothes = 1
Costume = 2
Other = 999
11. Type of shot:
DV: Type of Shot
Extreme Close-Up (XCU) = 1 (face)
Close-up (CU) = 2 (shoulders & up)
Wide shot (WS) = 3 (most of body)
12. Sexuality: ( scale of 1 to 5 with 1 being not sexual, to 5 being very sexual)
13. Brightness of colors on cover: (scale of 1 to 5 with 1 being dull/dark and 5 being "bright")
Once your hypotheses and variables are identified, go ahead and code your assigned covers. You'll most definitely run into problems. It's inevitable. Even so, do the best you can.
Once you have your data, you'll be able to run your statistical tests (remember that H1 needs to have nominal IV and DVs so that you can run a chi-square and that H2 needs to have a nominal IV and an Interval/Ratio DV so that you can run a t-test).
So, rather than a traditional final report, your final report will be this:
Introduction: (Why did you choose the hypotheses you did? What interested you? Why should we care?) (About 1 page)
Hypotheses: (List your two hypotheses; identify your IVs and DVs. Provide a theoretical rationale for each hypothesis. Provide conceptual definitions of your terms). (About 1-2 pages; you kind of already have this info with the assignment you completed; you can just cut and paste, though you want to make sure it flows with the rest of the document.)
Method: (Explain how you conducted a content analysis if EW covers. Talk about how it's a random sample taken from two years-- 1990 and 2013. This is where you provide the measurements (operational definitions). Often, you'll just say "I measured age by coding the relative age of the individuals on the cover using these categories (and then give the categories)." It's also in the methods' section where you identify which tests you'll use to test your hypotheses. (About 1-2 pages)
Results/Discussion: Indicate whether your hypotheses were supported or not. If supported, what do you think it means? How does this help us understand the world in which we live? If your hypotheses are NOT supported, why not? Why do you think it didn't work out as planned?
In addition, suggest some ideas for future researchers and discuss any problems you ran into (any limitations you might find). (About 1-2 pages)
That's it. The finished project should be about 5-8 pages-- that's a rough estimate. Yours may be less than that or more than that.
Once you're finished, send it to me via email. It's worth 100 points, so do the best you can.
Let me know if you have any questions.
Jack
1. Year of Magazine:
2. Issue # of magazine:
3. Number of people on cover:
4. Name of each individual on cover, if applicable:
5. Gender of each person: (1 = male; 2 = female)
6. Race of each individual, if applicable:
(1- White; 2- Black/African-American; 3-Hispanic; 4-Asian; 5-Other)
7. Age:
1 - 0-15 year olds
2 - 16-25 year olds
3 - 26-35 year olds
4 - 36-50 year olds
5 - 50+ year olds
(Instead of using these categories, you may want to use general categories like "child," "young adult," "middle age," "older adult," "elderly"). The goal is for your categories to make sense for what it is your examining.
8. Seriousness of actor: (5-point scale where 1 = not at all serious and 5 = very serious).
9. Smile:
1. no smile
2. slight smile
3. closed mouth smile (smirk)
4. open mouth smile (little teeth)
5. big, bright smile (many teeth)
10. Wardrobe:
Regular Clothes = 1
Costume = 2
Other = 999
11. Type of shot:
DV: Type of Shot
Extreme Close-Up (XCU) = 1 (face)
Close-up (CU) = 2 (shoulders & up)
Wide shot (WS) = 3 (most of body)
12. Sexuality: ( scale of 1 to 5 with 1 being not sexual, to 5 being very sexual)
13. Brightness of colors on cover: (scale of 1 to 5 with 1 being dull/dark and 5 being "bright")
Once your hypotheses and variables are identified, go ahead and code your assigned covers. You'll most definitely run into problems. It's inevitable. Even so, do the best you can.
Once you have your data, you'll be able to run your statistical tests (remember that H1 needs to have nominal IV and DVs so that you can run a chi-square and that H2 needs to have a nominal IV and an Interval/Ratio DV so that you can run a t-test).
So, rather than a traditional final report, your final report will be this:
Introduction: (Why did you choose the hypotheses you did? What interested you? Why should we care?) (About 1 page)
Hypotheses: (List your two hypotheses; identify your IVs and DVs. Provide a theoretical rationale for each hypothesis. Provide conceptual definitions of your terms). (About 1-2 pages; you kind of already have this info with the assignment you completed; you can just cut and paste, though you want to make sure it flows with the rest of the document.)
Method: (Explain how you conducted a content analysis if EW covers. Talk about how it's a random sample taken from two years-- 1990 and 2013. This is where you provide the measurements (operational definitions). Often, you'll just say "I measured age by coding the relative age of the individuals on the cover using these categories (and then give the categories)." It's also in the methods' section where you identify which tests you'll use to test your hypotheses. (About 1-2 pages)
Results/Discussion: Indicate whether your hypotheses were supported or not. If supported, what do you think it means? How does this help us understand the world in which we live? If your hypotheses are NOT supported, why not? Why do you think it didn't work out as planned?
In addition, suggest some ideas for future researchers and discuss any problems you ran into (any limitations you might find). (About 1-2 pages)
That's it. The finished project should be about 5-8 pages-- that's a rough estimate. Yours may be less than that or more than that.
Once you're finished, send it to me via email. It's worth 100 points, so do the best you can.
Let me know if you have any questions.
Jack
Step 1 of Completing your Project
Hi--
When it comes to content analysis, there are two types of information-- manifest and latent. Manifest means that it is readily apparent and latent means that you have to dig a little deeper.
Looking at whether a character on the cover of TV Guide is male, female, monster, etc. is manifest; Determining whether that character is portrayed positively or negatively is latent.
For our class project (which is really just a compendium of individual projects), we're going to analyze a representative sample of TV Guide magazine covers from 1990 through 2014.
How do we do this? Simple.
Let's do this--
Let's do a comparison of a random sample of TV Guide covers from the early 1990s to its last weekly complete year (2013).
(Beginning in 2014, TV Guide published once every 2 weeks instead of once every week).
In fact, let's just make it 1990 and 2013.
Each person will have to code magazine covers from TWO different years to analyze-- one from 1990 and one from 2013.
To select a random sample of magazine covers, we randomly choose a number, let's say "2" and then, beginning with the 2nd issue in 1990, we select every 2nd magazine cover as part of our sample.
Once the year ends, we repeat with the year 2013. This will give us about 26 magazine covers to examine for each year.
Here are a list of possible IVs:
Gender (male, female)
Age (child, young adult, middle age, older adult, senior)
Type of star (TV, movie, music, other, etc.)
Race/Ethnicity (we can simplify and just use the categories "Non-Minority," "Minority"-- otherwise, we open up a whole can of worms trying to figure out who's what...)
Smile (smiling or not smiling)
Year (1990 or 2008)
There are many others, of course, but that gives us a good start.
Possible DVs might include:
Skin exposure (scale of 1 to 5 where 1 is "little to no skin exposure" and 5 is "extreme skin exposure")
Skin color (scale of 1 to 5 where 1 is "light/pale skin" and 5 is "dark skin")
Sexuality (scale of 1 to 5 where 1 is not at all sexual and 5 is extremely sexual)
Smile (smiling or not smiling)
Hair color (scale of 1 to 5 where 1 is dark hair and 5 is blonde/light)
Age (same categories as above)
Any others you can think of...
This is definitely enough to get us going...
So here's what we're going to do. Each of you will complete the following form to help us determine our specific hypotheses.
After we have our hypotheses, we'll need to create the codebook (collectively) so that we know what we mean by each variable we're coding.
Here are two sample codebook items:
Gender: Gender refers to whether the individual(s) on the cover is/are male or female. If they are transgender, code as 3. If they are neither male/female nor transgender (such as a monster or something like that, please code as 999).
Male: 1
Female: 2
Transgender: 3
Other: 999
Age: Age refers to the general perception of where the individual featured on the cover is relative to others in our society. A child actor would be considered "young" and an actor such as Betty White would be considered "senior." Tom Cruise in 1990 might be considered "young adult," but Tom Cruise in 2013 might be considered "middle age."
1. Child
2. Young Adult
3. Middle Age
4. Older Adult
5. Senior
Get it?
So, to get started, here's a sample hypothesis:
TV Guide covers from 2013 are more likely to feature individuals with more skin exposure than those individuals featured on covers from 1990.
In this case, the IV is "year" and the DV is "skin exposure."
My rationale for this hypothesis is that we've become more accepting of skin exposure in mainstream media over the past 25 years. In addition, as more and more media compete, showing more skin might be a way to attract a larger audience, so it makes sense that we might see more skin exposure on today's covers than those covers from two decades ago.
Step 1 of completing your project, then, is to complete the following form and email it to me at jackpowers2@gmail.com.
I want your first hypothesis to have a nominal level of measurement for both the IV and the DV. Why? So that we can check for significance by solving for Chi-Square.
Here it is--
Name:
Hypothesis #1:
For your second hypothesis, I want your IV to be nominal and your DV to be Interval/Ratio. Why? So that we can check for significance by solving for t (t-test).
Hypothesis #2:
Let me know if you have any questions.
Peace,
Jack
When it comes to content analysis, there are two types of information-- manifest and latent. Manifest means that it is readily apparent and latent means that you have to dig a little deeper.
Looking at whether a character on the cover of TV Guide is male, female, monster, etc. is manifest; Determining whether that character is portrayed positively or negatively is latent.
For our class project (which is really just a compendium of individual projects), we're going to analyze a representative sample of TV Guide magazine covers from 1990 through 2014.
How do we do this? Simple.
Let's do this--
Let's do a comparison of a random sample of TV Guide covers from the early 1990s to its last weekly complete year (2013).
(Beginning in 2014, TV Guide published once every 2 weeks instead of once every week).
In fact, let's just make it 1990 and 2013.
Each person will have to code magazine covers from TWO different years to analyze-- one from 1990 and one from 2013.
To select a random sample of magazine covers, we randomly choose a number, let's say "2" and then, beginning with the 2nd issue in 1990, we select every 2nd magazine cover as part of our sample.
Once the year ends, we repeat with the year 2013. This will give us about 26 magazine covers to examine for each year.
Here are a list of possible IVs:
Gender (male, female)
Age (child, young adult, middle age, older adult, senior)
Type of star (TV, movie, music, other, etc.)
Race/Ethnicity (we can simplify and just use the categories "Non-Minority," "Minority"-- otherwise, we open up a whole can of worms trying to figure out who's what...)
Smile (smiling or not smiling)
Year (1990 or 2008)
There are many others, of course, but that gives us a good start.
Possible DVs might include:
Skin exposure (scale of 1 to 5 where 1 is "little to no skin exposure" and 5 is "extreme skin exposure")
Skin color (scale of 1 to 5 where 1 is "light/pale skin" and 5 is "dark skin")
Sexuality (scale of 1 to 5 where 1 is not at all sexual and 5 is extremely sexual)
Smile (smiling or not smiling)
Hair color (scale of 1 to 5 where 1 is dark hair and 5 is blonde/light)
Age (same categories as above)
Any others you can think of...
This is definitely enough to get us going...
So here's what we're going to do. Each of you will complete the following form to help us determine our specific hypotheses.
After we have our hypotheses, we'll need to create the codebook (collectively) so that we know what we mean by each variable we're coding.
Here are two sample codebook items:
Gender: Gender refers to whether the individual(s) on the cover is/are male or female. If they are transgender, code as 3. If they are neither male/female nor transgender (such as a monster or something like that, please code as 999).
Male: 1
Female: 2
Transgender: 3
Other: 999
Age: Age refers to the general perception of where the individual featured on the cover is relative to others in our society. A child actor would be considered "young" and an actor such as Betty White would be considered "senior." Tom Cruise in 1990 might be considered "young adult," but Tom Cruise in 2013 might be considered "middle age."
1. Child
2. Young Adult
3. Middle Age
4. Older Adult
5. Senior
Get it?
So, to get started, here's a sample hypothesis:
TV Guide covers from 2013 are more likely to feature individuals with more skin exposure than those individuals featured on covers from 1990.
In this case, the IV is "year" and the DV is "skin exposure."
My rationale for this hypothesis is that we've become more accepting of skin exposure in mainstream media over the past 25 years. In addition, as more and more media compete, showing more skin might be a way to attract a larger audience, so it makes sense that we might see more skin exposure on today's covers than those covers from two decades ago.
Step 1 of completing your project, then, is to complete the following form and email it to me at jackpowers2@gmail.com.
I want your first hypothesis to have a nominal level of measurement for both the IV and the DV. Why? So that we can check for significance by solving for Chi-Square.
Here it is--
Name:
Hypothesis #1:
- Independent variable:
- Dependent variable:
- Theoretical Rationale:
For your second hypothesis, I want your IV to be nominal and your DV to be Interval/Ratio. Why? So that we can check for significance by solving for t (t-test).
Hypothesis #2:
- Independent variable:
- Dependent variable:
- Theoretical Rationale:
Let me know if you have any questions.
Peace,
Jack
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