visibility study

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For this assignment, you will choose one television network (Netflix, Hulu, and Amazon Originals count in this category, but only originals). No student can choose a network that another student has chosen. They are first come, first served. Of the top ten shows on that channel (must verify with ratings and provide link), create a grid of the main characters (up to ten characters for each show). Using IMDb and other sources, determine the parentage of the actors: what is everyone’s race? On your grid, you will note each character’s 1) race and ethnicity in real life, 2) race/ethnicity on the show, 3) importance to the show’s story (scale of 1-10), 4) depiction (pos/neg/neutral/dynamic), and 5) one additional category that you think may be important for your data. You will examine the trends across shows. In a paper, you will discuss the overall representation, categorization, series impact, and larger social impact of mixed race people and characters. You must submit your data sheets along with your paper. Students will be required to make their selections (and inform Dr. Lê) by the deadline on Canvas.

Data Collection

20 points

After selecting a network that has been approved by Dr. Lê, create a list of the top ten current shows by ratings (must verify with ratings and provide link). You will be doing what is called a “content analysis” of the shows by use of a coding sheet (the “grid” mentioned above). This means that things need to be numerically and qualitatively recorded. Please follow the steps below:

Steps for the content analysis:

  • Determine a coding strategy to keep track of each* character’s 1) race and ethnicity in real life, 2) race/ethnicity on the show, 3) importance to the show’s story (scale of 1-10), 4) depiction (pos/neg/neutral/dynamic), and 5) one additional category that you think may be important for your data. You will count and/or describe the presence of these particular phenomena. *If there are many characters in the show, choose only the ten with the 1) most screen time or 2) most overall story importance.
  • Identify the character(s) of mixed race (real life and/or depicted)
  • You will need to submit your completed coding sheet(s) with your final paper (the coding sheet can be on paper and photographed or typed).

Analysis

70 points total

You will write up a 4-5 page paper with the following section headings and content:

Description and Data: briefly describe the network and shows in the analysis. List the series used. Provide counts/percentages of important variables (ex: “There were 98 characters across all shows with 87% of them portrayed as white. Despite this, 54% of the characters overall were actually mixed race, even if not depicted in such a way.”) Describe the mixed race (if any) actors’ role in the shows and how they are portrayed (also mention their true ancestry and racial and ethnic identitites). Describe the themes and issues you found during your content analysis.

Length suggestion: 1-2 pages; 30 points

Evaluation and Analysis: after describing the themes, place those in the context of what we have been learning. Analyze the previous themes and issues; examine across shows on your network. Some avenues of analysis are as follows:

  • Was there a lack of visibility? Was there a preponderance of visibility?
  • Ask yourself “why”—why were the mixed race actors (real life or depicted) represented in that way, etc. (to the questions from your coding sheet).
  • Who is the target audience for your shows? Does that change who the characters are based on your data?
  • How does your data highlight course concepts (be specific)? Are any theories or ideas from class applicable, and if so, how? Do your findings challenge or support what we have learned, or a bit of both? Be specific about in what ways it has using examples from the show.
  • Minimum two sources (lecture notes and at least one reading from the course) required.

Length suggestion: 2 pages; 40 points

Formatting Requirements

Use 12 point Arial font, one inch margins on all sides, double-spacing, and no title page. This should be formatted as an essay and not in bullet points or an outline. You may use APA, ASA, or MLA citation formatting. Your paper must include a reference list and in-text citations. Class lecture can be cited like the following: (class lecture x/x/2015) though should be cited sparingly as course readings should be the majority of references.

10 points

The more analysis you can provide within the page limit, the better—as it will demonstrate your ability to put course material into practice.

  • If you cannot write a full four pages, you may want to take your analysis deeper and go into more detail.
  • If you are struggling to condense your thoughts into five pages, you will want to write in a more concise, dense manner. Perhaps review the show descriptions and examples—shorten them as much as possible.

All papers must be submitted through our Canvas course by 11:59pm on the assigned due date.

Rubric

Mixed Race Visibility Study

Mixed Race Visibility Study

Criteria Ratings Pts

This criterion is linked to a Learning OutcomePaper: Description

10.0 pts

Excellent balance of concise and detailed synopsis of the show

7.5 pts

Too lengthy or too brief of a synopsis

5.0 pts

Very lacking in detail

0.0 pts

No Marks

10.0 pts

This criterion is linked to a Learning OutcomePaper: Data

20.0 pts

Precise recounting of show facts and external identity data

15.0 pts

Adequate presentation of show facts but lacking in specificity or missing external identity data

10.0 pts

Minimal data on show facts and/or no external identity data

0.0 pts

No Marks

20.0 pts

This criterion is linked to a Learning OutcomePaper: Evaluation and Analysis

40.0 pts

Expertly infused course material and advanced analysis with concrete examples from the show

30.0 pts

Applied some course material to analysis but the analysis was lacking in depth and precision

20.0 pts

Surface-level analysis

0.0 pts

No Marks

40.0 pts

This criterion is linked to a Learning OutcomePaper: Formatting

10.0 pts

Little to no errors

7.5 pts

Some errors

5.0 pts

Major errors

0.0 pts

No Marks

10.0 pts

This criterion is linked to a Learning OutcomeContent Analysis

20.0 pts

Excellent coding scheme with rich data

15.0 pts

Coding scheme was adequate but was lacking in depth and precision

10.0 pts

Minimal coding with little depth

0.0 pts

No Marks

20.0 pts

Total Points: 100.0

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