You are an expert in data visualization for M&E reporting. Score the charts and visualizations in the report I have attached or pasted using the rubric below. If the document contains text descriptions of charts rather than the charts themselves, score based on the descriptions. The goal is to assess whether visualizations communicate the data cleanly, accessibly, and honestly.
SCORING RUBRIC - Data Visualization Quality
Score each dimension 1-5 using these criteria:
DIMENSION 1: Chart Type Appropriateness
| 5 | Every chart type matches the data relationship it is showing. Bar charts for comparison across categories. Line charts for change over time. Stacked or 100 percent bars for composition. Scatter plots for relationships between two variables. Histograms or box plots for distribution. No chart is chosen for visual variety alone, and no chart misrepresents the underlying relationship. |
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| 4 | At least 80 percent of charts match the data. One or two chart-type mismatches but the message still survives. |
| 3 | Roughly half of charts match the data type cleanly. The rest are workable but suboptimal (e.g., pie charts used for many slices, line charts used for unordered categories, 3D effects on simple comparisons). |
| 2 | Most charts use the wrong chart type for what they are showing. Comparisons are muddled, trends are unclear, distributions are hidden. |
| 1 | Chart types actively obscure or misrepresent the data. The reader is worse off than reading the numbers in a table. |
DIMENSION 2: Labeling Completeness
| 5 | Every visualization has a clear, informative title (states what is shown, not just the variable name). Axes are labeled with units. Legends are present where multiple series exist. Data sources are named. Time periods are stated. The chart is interpretable on its own without the surrounding text. |
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| 4 | At least 80 percent of charts have complete labeling. A small number are missing one element (e.g., source citation or time period) but remain interpretable. |
| 3 | Roughly half of charts are well labeled. The rest are missing titles, units, sources, or legends. Reader has to consult surrounding text to understand the chart. |
| 2 | Most charts have weak or generic titles ("Figure 1"), missing axis units, or no legend. Many charts are not interpretable without rereading prose. |
| 1 | Charts are unlabeled or generically labeled. The reader cannot tell what is being shown without extensive context-hunting. |
DIMENSION 3: Honest Scaling
| 5 | Every chart uses honest axis choices. Y-axes start at zero for absolute comparisons unless there is a stated reason to truncate. Time-series intervals are consistent. Categories are ordered meaningfully (by value, time, or logic) rather than to flatter the message. Differences shown match differences in the data. No 3D effects, exploded slices, or warped scales exaggerate or minimize results. |
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| 4 | At least 80 percent of charts use honest scaling. One or two have a truncated axis or unusual interval but the issue is noted or does not change the takeaway. |
| 3 | Some scaling choices are questionable. Truncated y-axes without justification appear. Intervals are uneven without explanation. Pie or bar order is arbitrary. |
| 2 | Frequent scaling distortions. Y-axes truncated to amplify small differences, scales stretched, or 3D effects bias the read. The visual story diverges from the data story. |
| 1 | Scaling actively misleads. The charts tell a different story than the underlying numbers. |
DIMENSION 4: Accessibility
| 5 | All four elements present. Color palettes are colorblind-safe (no red-green only). Contrast between data series and background is sufficient. Color is never the only signal: pattern, shape, label, or direct annotation reinforces the meaning. Visualizations remain legible at the report's likely print or screen size. |
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| 4 | At least three of four elements present. Color is mostly safe and labeled, with one or two charts where contrast or pairing is partial. |
| 3 | Some accessibility considered but inconsistently applied. Color is sometimes the only signal. Contrast varies. |
| 2 | Accessibility largely absent. Colors are arbitrary, contrast is low, and color is the only way to distinguish series in most charts. |
| 1 | Charts are inaccessible. Color-blind readers, low-vision readers, or readers viewing in grayscale lose key information. |
DIMENSION 5: Caption Quality
| 5 | Every visualization has a caption that interprets the data. The caption tells the reader what to take away (the pattern, the comparison, the surprise) rather than only describing what is in the chart. Captions are concise (one or two sentences) and tie the visualization to the surrounding analysis. |
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| 4 | At least 80 percent of captions interpret. A few are descriptive only but the key charts are anchored. |
| 3 | Roughly half of captions interpret; the rest describe ("Figure 2 shows survey responses by region") without telling the reader what to notice. |
| 2 | Most captions are descriptive labels. Few connect the visualization to a takeaway. |
| 1 | Captions are missing or limited to figure numbers. Reader has no guidance about what to make of each chart. |
OUTPUT FORMAT:
Return your assessment as a table followed by a summary:
| Dimension | Score (1-5) | Evidence | Priority Revision |
|---|---|---|---|
| Chart Type Appropriateness | |||
| Labeling Completeness | |||
| Honest Scaling | |||
| Accessibility | |||
| Caption Quality |
Total: X/25 Band: Strong (22-25) / Adequate (17-21) / Needs Revision (11-16) / Substantial Revision (5-10) Single Most Important Revision: [One specific sentence]
For any dimension scored 1 or 2, add a brief explanation and a concrete revision example using one of the visualizations in the document.
REPORT (OR VIZ DESCRIPTIONS) TO SCORE:
(See the attached or pasted document.)
Document to review: Attached, or pasted below. Base everything above on it and do not invent details that are not in it.