COU 4: Depicting Policy Polarization and Partisan Divergence

In this exercise, you’ll practice using the tools you’ve learned in the lesson so far to represent policy polarization and partisan divergence in a small group of persons. You’ll do so using a graph like this:

{
  const facetHeight = 500
  const facetMargin = {top: 10, right: 40, bottom: 50, left: 40}
  const pScale = d3.scaleLinear()
        .domain([0,1])
        .range([facetMargin.left, width - facetMargin.right])
  const pctScale = d3.scaleLinear()
        .domain([0,100])
        .range([facetHeight-facetMargin.bottom, facetMargin.top+10])
  const view = htl.html`
    <style>
      .spatial-display {
        border: 1px solid lightgray;
        border-radius: 10px;
        padding: 10px 30px 10px 30px;
        display: flex;
        flex-direction: column;
        align-items: center;
      }
      svg {
        font: 20px sans-serif;
      }
      .bin-pct {
        font: 10px sans-serif;
      }
      .member-label {
        font: 14px sans-serif !important;
      }
      .median-label {
        font: 14px sans-serif !important;   
      }
      .facet-title {
        font: 16px sans-serif !important;
        font-weight: 900 !important;
      }
      .yaxis-tick-label {
        font: 10px sans-serif;
      }
    </style>
    <div class="spatial-display">
      <svg viewBox="0 0 ${width} ${facetHeight}" >
          <path d=${d3.line()([[pScale(0),pctScale(0)],[pScale(1),pctScale(0)]])} stroke="black" fill="none" stroke-width="6px" stroke-linecap="round" />
          ${Array.from({length: 21}, (el,idx) => (idx)/20).map(cut => htl.svg`
            <path d=${d3.line()([[pScale(cut),pctScale(0)],[pScale(cut), pctScale(100)]])} stroke="gray" fill="none" stroke-width="1px" stroke-dasharray="4 1"/>
            <path d=${d3.line()([[pScale(cut),pctScale(0)],[pScale(cut), pctScale(0) + 0.25*facetMargin.bottom]])} stroke="black" fill="none" stroke-width="1px"/>
          `)}         
          ${Array.from({length: 20}, (el,idx) => 100*(idx+1)/20).map(cut => htl.svg`
            <path d=${d3.line()([[pScale(0),pctScale(cut)],[pScale(1), pctScale(cut)]])} stroke="gray" fill="none" stroke-width="1px" stroke-dasharray="4 1"/>
            <path d=${d3.line()([[pScale(0),pctScale(cut)],[pScale(0)-0.25*facetMargin.left, pctScale(cut)]])} stroke="black" fill="none" stroke-width="1px" />
            <text x=${pScale(0) - 0.25*facetMargin.left} y=${pctScale(cut)+5} text-anchor="end" class="yaxis-tick-label">${d3.format(".0%")(cut/100)}</text>
          `)}
      </svg>
    </div>
  `
  return view;
}

The thick black line at the bottom of this graph represents a policy space, along which you can draw ideal points of persons like so:

{
  const idealPoints = [0.03, 0.32, 0.34, 0.82, 0.87]
  const labels = [1,2,3,4,5]
  const facetHeight = 500
  const facetMargin = {top: 10, right: 40, bottom: 50, left: 40}
  const pScale = d3.scaleLinear()
        .domain([0,1])
        .range([facetMargin.left, width - facetMargin.right])
  const pctScale = d3.scaleLinear()
        .domain([0,100])
        .range([facetHeight-facetMargin.bottom, facetMargin.top+10])
  const view = htl.html`
    <style>
      .spatial-display {
        border: 1px solid lightgray;
        border-radius: 10px;
        padding: 10px 30px 10px 30px;
        display: flex;
        flex-direction: column;
        align-items: center;
      }
      svg {
        font: 20px sans-serif;
      }
      .bin-pct {
        font: 10px sans-serif;
      }
      .member-label {
        font: 14px sans-serif !important;
      }
      .median-label {
        font: 14px sans-serif !important;   
      }
      .facet-title {
        font: 16px sans-serif !important;
        font-weight: 900 !important;
      }
      .yaxis-tick-label {
        font: 10px sans-serif;
      }
    </style>
    <div class="spatial-display">
      <svg viewBox="0 0 ${width} ${facetHeight}" >
          <path d=${d3.line()([[pScale(0),pctScale(0)],[pScale(1),pctScale(0)]])} stroke="black" fill="none" stroke-width="6px" stroke-linecap="round" />
          ${Array.from({length: 21}, (el,idx) => (idx)/20).map(cut => htl.svg`
            <path d=${d3.line()([[pScale(cut),pctScale(0)],[pScale(cut), pctScale(100)]])} stroke="gray" fill="none" stroke-width="1px" stroke-dasharray="4 1"/>
            <path d=${d3.line()([[pScale(cut),pctScale(0)],[pScale(cut), pctScale(0) + 0.25*facetMargin.bottom]])} stroke="black" fill="none" stroke-width="1px"/>
          `)}         
          ${Array.from({length: 20}, (el,idx) => 100*(idx+1)/20).map(cut => htl.svg`
            <path d=${d3.line()([[pScale(0),pctScale(cut)],[pScale(1), pctScale(cut)]])} stroke="gray" fill="none" stroke-width="1px" stroke-dasharray="4 1"/>
            <path d=${d3.line()([[pScale(0),pctScale(cut)],[pScale(0)-0.25*facetMargin.left, pctScale(cut)]])} stroke="black" fill="none" stroke-width="1px" />
            <text x=${pScale(0) - 0.25*facetMargin.left} y=${pctScale(cut)+5} text-anchor="end" class="yaxis-tick-label">${d3.format(".0%")(cut/100)}</text>
          `)}
          ${Array.from({length: 5}, (el,idx) => idx).map(el => htl.svg`
            <path d=${d3.line()([[pScale(idealPoints[el]),pctScale(0)],[pScale(idealPoints[el]),pctScale(0) + 0.5*facetMargin.bottom]])} stroke="black" fill="none" stroke-width="2px" />
            <circle cx=${pScale(idealPoints[el])} cy=${pctScale(0) + 0.5*facetMargin.bottom} r=${0.25*facetMargin.bottom} fill="white" stroke="black" />
            <text x=${pScale(idealPoints[el])} y=${pctScale(0) + (0.5+0.1)*facetMargin.bottom} text-anchor="middle" class="member-label">${labels[el]}</text>
          `)}
      </svg>
    </div>
  `
  return view;
}

The tick marks along the policy space break it up into 20 equally-sized segments. We can show the distribution of the group’s ideal points by shading the column above each segment up to the level on the vertical axis indicating the percentage of the group whose ideal points are located in that segment.

For instance, we’ve drawn the ideal points of five persons above, so each person represents \text{$\frac{1}{5}$th} or 20% of the group. Only one person, person 1, is in the far-left segment, so we’ll shade the column above that segment up to the 20% line on the vertical axis like so:

{
  const idealPoints = [0.03, 0.32, 0.34, 0.82, 0.87]
  const labels = [1,2,3,4,5]
  const facetHeight = 500
  const facetMargin = {top: 10, right: 40, bottom: 50, left: 40}
  const pScale = d3.scaleLinear()
        .domain([0,1])
        .range([facetMargin.left, width - facetMargin.right])
  const pctScale = d3.scaleLinear()
        .domain([0,100])
        .range([facetHeight-facetMargin.bottom, facetMargin.top+10])
  const view = htl.html`
    <style>
      .spatial-display {
        border: 1px solid lightgray;
        border-radius: 10px;
        padding: 10px 30px 10px 30px;
        display: flex;
        flex-direction: column;
        align-items: center;
      }
      svg {
        font: 20px sans-serif;
      }
      .bin-pct {
        font: 10px sans-serif;
      }
      .member-label {
        font: 14px sans-serif !important;
      }
      .median-label {
        font: 14px sans-serif !important;   
      }
      .facet-title {
        font: 16px sans-serif !important;
        font-weight: 900 !important;
      }
      .yaxis-tick-label {
        font: 10px sans-serif;
      }
    </style>
    <div class="spatial-display">
      <svg viewBox="0 0 ${width} ${facetHeight}" >
          <rect x=${pScale(0)} y=${pctScale(20)} width=${pScale(0.05)-pScale(0)} height=${pctScale(0)-pctScale(20)} stroke="none" fill="lightgray" />
          <path d=${d3.line()([[pScale(0),pctScale(0)],[pScale(1),pctScale(0)]])} stroke="black" fill="none" stroke-width="6px" stroke-linecap="round" />
          ${Array.from({length: 21}, (el,idx) => (idx)/20).map(cut => htl.svg`
            <path d=${d3.line()([[pScale(cut),pctScale(0)],[pScale(cut), pctScale(100)]])} stroke="gray" fill="none" stroke-width="1px" stroke-dasharray="4 1"/>
            <path d=${d3.line()([[pScale(cut),pctScale(0)],[pScale(cut), pctScale(0) + 0.25*facetMargin.bottom]])} stroke="black" fill="none" stroke-width="1px"/>
          `)}         
          ${Array.from({length: 20}, (el,idx) => 100*(idx+1)/20).map(cut => htl.svg`
            <path d=${d3.line()([[pScale(0),pctScale(cut)],[pScale(1), pctScale(cut)]])} stroke="gray" fill="none" stroke-width="1px" stroke-dasharray="4 1"/>
            <path d=${d3.line()([[pScale(0),pctScale(cut)],[pScale(0)-0.25*facetMargin.left, pctScale(cut)]])} stroke="black" fill="none" stroke-width="1px" />
            <text x=${pScale(0) - 0.25*facetMargin.left} y=${pctScale(cut)+5} text-anchor="end" class="yaxis-tick-label">${d3.format(".0%")(cut/100)}</text>
          `)}
          ${Array.from({length: 5}, (el,idx) => idx).map(el => htl.svg`
            <path d=${d3.line()([[pScale(idealPoints[el]),pctScale(0)],[pScale(idealPoints[el]),pctScale(0) + 0.5*facetMargin.bottom]])} stroke="black" fill="none" stroke-width="2px" />
            <circle cx=${pScale(idealPoints[el])} cy=${pctScale(0) + 0.5*facetMargin.bottom} r=${0.25*facetMargin.bottom} fill="white" stroke="black" />
            <text x=${pScale(idealPoints[el])} y=${pctScale(0) + (0.5+0.1)*facetMargin.bottom} text-anchor="middle" class="member-label">${labels[el]}</text>
          `)}
      </svg>
    </div>
  `
  return view;
}

Person 2’s and person 3’s ideal points sit together in a single segment of the space. They make up \text{$\frac{2}{5}$ths} or 40% of the group, and so we’ll shade the column above their ideal points up to the 40% level like so:

{
  const idealPoints = [0.03, 0.32, 0.34, 0.82, 0.87]
  const labels = [1,2,3,4,5]
  const facetHeight = 500
  const facetMargin = {top: 10, right: 40, bottom: 50, left: 40}
  const pScale = d3.scaleLinear()
        .domain([0,1])
        .range([facetMargin.left, width - facetMargin.right])
  const pctScale = d3.scaleLinear()
        .domain([0,100])
        .range([facetHeight-facetMargin.bottom, facetMargin.top+10])
  const view = htl.html`
    <style>
      .spatial-display {
        border: 1px solid lightgray;
        border-radius: 10px;
        padding: 10px 30px 10px 30px;
        display: flex;
        flex-direction: column;
        align-items: center;
      }
      svg {
        font: 20px sans-serif;
      }
      .bin-pct {
        font: 10px sans-serif;
      }
      .member-label {
        font: 14px sans-serif !important;
      }
      .median-label {
        font: 14px sans-serif !important;   
      }
      .facet-title {
        font: 16px sans-serif !important;
        font-weight: 900 !important;
      }
      .yaxis-tick-label {
        font: 10px sans-serif;
      }
    </style>
    <div class="spatial-display">
      <svg viewBox="0 0 ${width} ${facetHeight}" >
          <rect x=${pScale(0)} y=${pctScale(20)} width=${pScale(0.05)-pScale(0)} height=${pctScale(0)-pctScale(20)} stroke="none" fill="lightgray" />
          <rect x=${pScale(0.3)} y=${pctScale(40)} width=${pScale(0.05)-pScale(0)} height=${pctScale(0)-pctScale(40)} stroke="none" fill="lightgray" />
          <path d=${d3.line()([[pScale(0),pctScale(0)],[pScale(1),pctScale(0)]])} stroke="black" fill="none" stroke-width="6px" stroke-linecap="round" />
          ${Array.from({length: 21}, (el,idx) => (idx)/20).map(cut => htl.svg`
            <path d=${d3.line()([[pScale(cut),pctScale(0)],[pScale(cut), pctScale(100)]])} stroke="gray" fill="none" stroke-width="1px" stroke-dasharray="4 1"/>
            <path d=${d3.line()([[pScale(cut),pctScale(0)],[pScale(cut), pctScale(0) + 0.25*facetMargin.bottom]])} stroke="black" fill="none" stroke-width="1px"/>
          `)}         
          ${Array.from({length: 20}, (el,idx) => 100*(idx+1)/20).map(cut => htl.svg`
            <path d=${d3.line()([[pScale(0),pctScale(cut)],[pScale(1), pctScale(cut)]])} stroke="gray" fill="none" stroke-width="1px" stroke-dasharray="4 1"/>
            <path d=${d3.line()([[pScale(0),pctScale(cut)],[pScale(0)-0.25*facetMargin.left, pctScale(cut)]])} stroke="black" fill="none" stroke-width="1px" />
            <text x=${pScale(0) - 0.25*facetMargin.left} y=${pctScale(cut)+5} text-anchor="end" class="yaxis-tick-label">${d3.format(".0%")(cut/100)}</text>
          `)}
          ${Array.from({length: 5}, (el,idx) => idx).map(el => htl.svg`
            <path d=${d3.line()([[pScale(idealPoints[el]),pctScale(0)],[pScale(idealPoints[el]),pctScale(0) + 0.5*facetMargin.bottom]])} stroke="black" fill="none" stroke-width="2px" />
            <circle cx=${pScale(idealPoints[el])} cy=${pctScale(0) + 0.5*facetMargin.bottom} r=${0.25*facetMargin.bottom} fill="white" stroke="black" />
            <text x=${pScale(idealPoints[el])} y=${pctScale(0) + (0.5+0.1)*facetMargin.bottom} text-anchor="middle" class="member-label">${labels[el]}</text>
          `)}
      </svg>
    </div>
  `
  return view;
}

Like person 1’s ideal point, person 4’s and persons 5’s ideal points each sit alone in one segment. So we’ll shade the columns above each of those segments up to the 20% level to complete our depiction of the distribution of the group’s ideal points.

{
  const idealPoints = [0.03, 0.32, 0.34, 0.82, 0.87]
  const labels = [1,2,3,4,5]
  const facetHeight = 500
  const facetMargin = {top: 10, right: 40, bottom: 50, left: 40}
  const pScale = d3.scaleLinear()
        .domain([0,1])
        .range([facetMargin.left, width - facetMargin.right])
  const pctScale = d3.scaleLinear()
        .domain([0,100])
        .range([facetHeight-facetMargin.bottom, facetMargin.top+10])
  const view = htl.html`
    <style>
      .spatial-display {
        border: 1px solid lightgray;
        border-radius: 10px;
        padding: 10px 30px 10px 30px;
        display: flex;
        flex-direction: column;
        align-items: center;
      }
      svg {
        font: 20px sans-serif;
      }
      .bin-pct {
        font: 10px sans-serif;
      }
      .member-label {
        font: 14px sans-serif !important;
      }
      .median-label {
        font: 14px sans-serif !important;   
      }
      .facet-title {
        font: 16px sans-serif !important;
        font-weight: 900 !important;
      }
      .yaxis-tick-label {
        font: 10px sans-serif;
      }
    </style>
    <div class="spatial-display">
      <svg viewBox="0 0 ${width} ${facetHeight}" >
          <rect x=${pScale(0)} y=${pctScale(20)} width=${pScale(0.05)-pScale(0)} height=${pctScale(0)-pctScale(20)} stroke="none" fill="lightgray" />
          <rect x=${pScale(0.3)} y=${pctScale(40)} width=${pScale(0.05)-pScale(0)} height=${pctScale(0)-pctScale(40)} stroke="none" fill="lightgray" />
          <rect x=${pScale(0.80)} y=${pctScale(20)} width=${pScale(0.05)-pScale(0)} height=${pctScale(0)-pctScale(20)} stroke="none" fill="lightgray" />
          <rect x=${pScale(0.85)} y=${pctScale(20)} width=${pScale(0.05)-pScale(0)} height=${pctScale(0)-pctScale(20)} stroke="none" fill="lightgray" />
          <path d=${d3.line()([[pScale(0),pctScale(0)],[pScale(1),pctScale(0)]])} stroke="black" fill="none" stroke-width="6px" stroke-linecap="round" />
          ${Array.from({length: 21}, (el,idx) => (idx)/20).map(cut => htl.svg`
            <path d=${d3.line()([[pScale(cut),pctScale(0)],[pScale(cut), pctScale(100)]])} stroke="gray" fill="none" stroke-width="1px" stroke-dasharray="4 1"/>
            <path d=${d3.line()([[pScale(cut),pctScale(0)],[pScale(cut), pctScale(0) + 0.25*facetMargin.bottom]])} stroke="black" fill="none" stroke-width="1px"/>
          `)}         
          ${Array.from({length: 20}, (el,idx) => 100*(idx+1)/20).map(cut => htl.svg`
            <path d=${d3.line()([[pScale(0),pctScale(cut)],[pScale(1), pctScale(cut)]])} stroke="gray" fill="none" stroke-width="1px" stroke-dasharray="4 1"/>
            <path d=${d3.line()([[pScale(0),pctScale(cut)],[pScale(0)-0.25*facetMargin.left, pctScale(cut)]])} stroke="black" fill="none" stroke-width="1px" />
            <text x=${pScale(0) - 0.25*facetMargin.left} y=${pctScale(cut)+5} text-anchor="end" class="yaxis-tick-label">${d3.format(".0%")(cut/100)}</text>
          `)}
          ${Array.from({length: 5}, (el,idx) => idx).map(el => htl.svg`
            <path d=${d3.line()([[pScale(idealPoints[el]),pctScale(0)],[pScale(idealPoints[el]),pctScale(0) + 0.5*facetMargin.bottom]])} stroke="black" fill="none" stroke-width="2px" />
            <circle cx=${pScale(idealPoints[el])} cy=${pctScale(0) + 0.5*facetMargin.bottom} r=${0.25*facetMargin.bottom} fill="white" stroke="black" />
            <text x=${pScale(idealPoints[el])} y=${pctScale(0) + (0.5+0.1)*facetMargin.bottom} text-anchor="middle" class="member-label">${labels[el]}</text>
          `)}
      </svg>
    </div>
  `
  return view;
}

Instructions

This COU is broken up into several prompts. Each prompt asks you to draw a single diagram using the grid above. Download this pdf of the grid and print several copies. Then, to answer each prompt, you can draw ideal points and shade the grid as needed by hand on one of your blank printed copies. To submit your answer to each prompt, scan your hand-drawn diagram by following Gradescope’s scanning instructions, then upload your scan to Gradescope.

Prompt 1

Draw the ideal points of twelve persons, shading the grid as described above to show the distribution of the ideal points in the group. Distribute the twelve ideal points across the space so that the group has no or a very low level of policy polarization.

Prompt 2

Prompt 3A

In this and the next two prompts (3B and 3C), you’ll show a group of thirty persons, each of whom belong to one of two political parties, “Party A” and “Party B”. Fifteen of the persons must be members of Party A, and the other fifteen must be members of Party B.

You must distribute the ideal points of the group so that the group as a whole has high level of partisan divergence. You’ll show this by…

First, in this prompt (Prompt 3A), drawing a graph that shows the ideal points of all thirty members of the group, shading the grid to show the distribution of ideal points for the group as a whole.
Second, in the next prompt (Prompt 3B), drawing a graph that shows the ideal points of only the fifteen members of the group who belong to Party A.
Third, in the next prompt after that (Prompt 3C), drawing a graph that shows the ideal points of only the fifteen members of the group who belong to party B.

In graphs you draw in response to each of the three prompts, add labels to the ideal points showing which belong to members of Party A and which belong to members of Party B. For instance, here’s a diagram of a group consisting of two persons, one of whom is labeled as a member of Party A and the other of which is labeled as a member of Party B:

{
  const idealPoints = [0.32, 0.82]
  const labels = [1,2]
  const parties = ["A","B"]
  const facetHeight = 500
  const facetMargin = {top: 10, right: 40, bottom: 60, left: 40}
  const pScale = d3.scaleLinear()
        .domain([0,1])
        .range([facetMargin.left, width - facetMargin.right])
  const pctScale = d3.scaleLinear()
        .domain([0,100])
        .range([facetHeight-facetMargin.bottom, facetMargin.top+10])
  const view = htl.html`
    <style>
      .spatial-display {
        border: 1px solid lightgray;
        border-radius: 10px;
        padding: 10px 30px 10px 30px;
        display: flex;
        flex-direction: column;
        align-items: center;
      }
      svg {
        font: 20px sans-serif;
      }
      .bin-pct {
        font: 10px sans-serif;
      }
      .member-label {
        font: 14px sans-serif !important;
      }
      .median-label {
        font: 14px sans-serif !important;   
      }
      .facet-title {
        font: 16px sans-serif !important;
        font-weight: 900 !important;
      }
      .yaxis-tick-label {
        font: 10px sans-serif;
      }
    </style>
    <div class="spatial-display">
      <svg viewBox="0 0 ${width} ${facetHeight}" >
          <rect x=${pScale(0.3)} y=${pctScale(50)} width=${pScale(0.05)-pScale(0)} height=${pctScale(0)-pctScale(50)} stroke="none" fill="lightgray" />
          <rect x=${pScale(0.8)} y=${pctScale(50)} width=${pScale(0.05)-pScale(0)} height=${pctScale(0)-pctScale(50)} stroke="none" fill="lightgray" />
          <path d=${d3.line()([[pScale(0),pctScale(0)],[pScale(1),pctScale(0)]])} stroke="black" fill="none" stroke-width="6px" stroke-linecap="round" />
          ${Array.from({length: 21}, (el,idx) => (idx)/20).map(cut => htl.svg`
            <path d=${d3.line()([[pScale(cut),pctScale(0)],[pScale(cut), pctScale(100)]])} stroke="gray" fill="none" stroke-width="1px" stroke-dasharray="4 1"/>
            <path d=${d3.line()([[pScale(cut),pctScale(0)],[pScale(cut), pctScale(0) + 0.25*facetMargin.bottom]])} stroke="black" fill="none" stroke-width="1px"/>
          `)}         
          ${Array.from({length: 20}, (el,idx) => 100*(idx+1)/20).map(cut => htl.svg`
            <path d=${d3.line()([[pScale(0),pctScale(cut)],[pScale(1), pctScale(cut)]])} stroke="gray" fill="none" stroke-width="1px" stroke-dasharray="4 1"/>
            <path d=${d3.line()([[pScale(0),pctScale(cut)],[pScale(0)-0.25*facetMargin.left, pctScale(cut)]])} stroke="black" fill="none" stroke-width="1px" />
            <text x=${pScale(0) - 0.25*facetMargin.left} y=${pctScale(cut)+5} text-anchor="end" class="yaxis-tick-label">${d3.format(".0%")(cut/100)}</text>
          `)}
          ${Array.from({length: 2}, (el,idx) => idx).map(el => htl.svg`
            <path d=${d3.line()([[pScale(idealPoints[el]),pctScale(0)],[pScale(idealPoints[el]),pctScale(0) + 0.5*facetMargin.bottom]])} stroke="black" fill="none" stroke-width="2px" />
            <circle cx=${pScale(idealPoints[el])} cy=${pctScale(0) + 0.5*facetMargin.bottom} r=${0.25*facetMargin.bottom} fill="white" stroke="black" />
            <text x=${pScale(idealPoints[el])} y=${pctScale(0) + (0.5+0.1)*facetMargin.bottom} text-anchor="middle" class="member-label">${labels[el]}</text>
            <text x=${pScale(idealPoints[el])} y=${facetHeight} text-anchor="middle" class="member-label">${parties[el]}</text>
          `)}
      </svg>
    </div>
  `
  return view;
}

OK, with all that in mind, respond to Prompt 3A with a graph that shows the distribution of ideal points of all thirty members of the group, with each ideal point labeled to show the party of the relevant group member. Again, distribute the group members so that it is evident from your responses to prompts 3A, 3B and 3C that the group has a high level of partisan divergence.

Prompt 3B

Draw a graph that shows the ideal points of only of the fifteen members of Party A from the group of thirty persons you graphed in your response to Prompt 3A.

Keep in mind that since you are graphing the members of Party A from exactly the same group of persons you graphed in your response to 3A, the ideal point for each person included in this graph must be located in the same place as the ideal points of that persons from your submission to 3A.

Also, when shading the grid to show the distribution of the ideal points of these fifteen group members, keep in mind that this chart should show the percentage of the members of Party A with ideal points in each segment of the policy space. In contrast, your submission for 3A showed the percentage of ideal points of the entire group in each segment. For instance, if five members of the group as a whole have ideal points in a given segment, two of whom are members of Party A and three of whom are members of Party B, the percentage of the group as a whole with ideal points in that segment is 100\times\frac{5}{30} \approx 17\%, the percentage of Party A with ideal points in that segment is 100\times\frac{2}{15}\approx 13\% and the percentage of Party B with ideal points in that segment is 100\times\frac{3}{15}=20\%.

Prompt 3C

Draw a graph that shows the ideal points of only of the fifteen members of Party B from the group of thirty persons you graphed in your response to Prompt 3A.

Keep in mind that since you are graphing the members of Party B from exactly the same group of persons you graphed in your response to 3A, the ideal point for each person included in this graph must be located in the same place as the ideal points of that persons from your submission to 3A.

Prompt 4A

In this and the next two prompts, you’ll show a group of 30 persons, 15 of whom are members of Party A and 15 of whom are members of Party B. Specifically, you show all 30 group members in your response to Prompt 4A, the 15 members of the group who belong to Party A in response to Prompt 4B, and the 15 members of the group who belong to Party B in your response to Prompt 4C.

Unlike your responses to Prompts 3A, 3B and 3C, the graphs you submit for 4A, 4B and 4C must show a group that has a high level of partisan divergence and no or a low level of policy polarization.

OK, with all that in mind, submit a graph showing all 30 members of the group. Label each ideal point indicating the party to which the relevant person belongs. The shaded bars should indicate the percentage of the group as a whole with ideal points located within each segment of the policy space.

Prompt 4B

Submit a graph showing the ideal points of only the persons from your submission to Prompt 4A who belong to Party A. The shaded portions of the graph must show the percentage of members of Party A (not the percentage of the group as a whole!) whose ideal points are located within each segment.

Prompt 4C

Submit a graph showing the ideal points of only the persons from your submission to Prompt 4A who belong to Party B. The shaded portions of the graph must show the percentage of members of Party B (not the percentage of the group as a whole!) whose ideal points are located within each segment.

Prompt 5A

In this and the next two prompts, you’ll show a group of 30 persons, 15 of whom are members of Party A and 15 of whom are members of Party B. Specifically, you show all 30 group members in your response to Prompt 5A, the 15 members of the group who belong to Party A in response to Prompt 5B, and the 15 members of the group who belong to Party B in your response to Prompt 5C.

Unlike your responses to Prompts 4A, 4B and 4C, the graphs you submit for 5A, 5B and 5C must show a group that has a high level of partisan divergence and high level of policy polarization.

Prompt 5B

Submit a graph showing the ideal points of only the persons from your submission to Prompt 5A who belong to Party A. The shaded portions of the graph must show the percentage of members of Party A (not the percentage of the group as a whole!) whose ideal points are located within each segment.

Prompt 5C

Submit a graph showing the ideal points of only the persons from your submission to Prompt 5A who belong to Party B. The shaded portions of the graph must show the percentage of members of Party B (not the percentage of the group as a whole!) whose ideal points are located within each segment.

Rubric

Prompts 1 and 2

You can earn up to 1 point on each of prompts 1 and 2.

On each prompt, you get 1 point if…

Your graph shows the ideal points of 12 persons
You graph shades the column above each of the 20 segments of the policy space up to the level indicating the percentage of the 12 persons who have ideal points in that segment.
The ideal points in your graph are distributed in a way that exhibits the level of policy polarization specified in the prompt (no or low for Prompt 1, high for Prompt 2).

On each prompt, you get 0.5 points if you’re graph satisfies criterion (c) but is partially but not completely incorrect on ONE of either criterion (a) or (b) and wholly correct on the other of those two criteria.

On each prompt, you get 0 points if your graph is in any way incorrect in satisfying each of criteria (a) and (b) OR if your graph fails to satisfy (c).

Prompts 3A through 5C

Prompts 3A through 5C are grouped into three sets – Prompts 3A-3C, Prompts 4A-4C and Prompts 5A-5C. You can earn up to 1 point on each set.

To get 1 point on a set, the three graphs you submit in response to the prompts in that set must meet all the requirements for that set (e.g. labeling the party attached to each ideal point, graphing the correct percentage of the relevant group in each segment, showing the correct set of members in response to each prompt, etc.) AND the three graphs together must show the level of policy polarization and/or partisan divergence requested for that set.

You get 0.5 points on a set if there are no more than 2 minor errors in the construction of the graphs but the required level of policy polarization and/or partisan divergence is still evident in the graphs as a whole

You get 0 points on a set if you have more than 2 minor errors in the graphs you submit OR if you wholly miss any required element on any of the graphs OR if the level of policy polarization and/or partisan divergence is not evident.