Work the five delivered sources into the pages

The source-request loop paid for itself immediately — two of the five
corrected something rather than confirming it.

The Economist piece settles V1, the riskiest live claim, but our note
had over-claimed: truncating the scale is its *first* example, not one
of "several." Note rewritten to quote her. The same article turned out
to contain a dual-axis chart she caught herself on, now cited.

Datawrapper's color-scale part 1 refuted the assumption behind a queued
sin outright: it makes no argument against rainbow scales and endorses
multi-hue sequential gradients. The rainbow entry is now marked as
having no verified source at all, rather than ample backing.

The dual-axis post independently draws the same line we drew last turn
— of four uses only the alternative-scale case survives, their example
being F against C — and led to two references worth more than the blog
post: the Isenberg et al. study that tested dual-scale charts, and Few's
article working through the cases. Both ship without full metadata
rather than guessed metadata; queued.

Pie and stacked posts gave verbatim support, plus one correction: a
100%-stacked chart has two readable baselines, not one.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01ULE5RRxdQE1ebwefEd2eCM

docs/content-backlog.md

@@ -17,7 +17,7 @@ runs 2–5 on purpose.
 
 ## Sources in play
 
-`src/lib/references.ts` currently holds 22 entries, 18 of them cited by the five
+`src/lib/references.ts` currently holds 24 entries, 20 of them cited by the five
 published sins. This table is a **convenience, not a scoreboard** — it's here so
 you can spot a source that fits a sin you're drafting, not so we can drive the
 right-hand column to zero blanks. An uncited reference is not a debt.
@@ -31,9 +31,10 @@ seven sources, give it seven and add whatever's missing to the file.
 | `healy` | — |
 | `munzner` | — |
 | `schwabish` | — |
-| `datawrapper` | dual-axis-correlation |
+| `fewdualaxes` | dual-axis-correlation |
 | `fewpies` | too-many-pie-slices |
 | `huff` | truncated-y-axis |
+| `isenberg2011` | dual-axis-correlation |
 | `shapeparameter` | aspect-ratio |
 | `showmenumbers` | too-many-pie-slices |
 | `spurious` | dual-axis-correlation |
@@ -42,12 +43,13 @@ seven sources, give it seven and add whatever's missing to the file.
 | `vizwtf` | inverted-y-axis |
 | `callingbullshit` | inverted-y-axis, truncated-y-axis |
 | `datatoviz` | dual-axis-correlation, too-many-pie-slices |
+| `datawrapper` | dual-axis-correlation, too-many-pie-slices |
 | `eagereyes` | aspect-ratio, too-many-pie-slices |
-| `economistmistakes` | inverted-y-axis, truncated-y-axis |
 | `junkcharts` | inverted-y-axis, too-many-pie-slices |
 | `truthfulart` | aspect-ratio, dual-axis-correlation |
 | `wilke` | too-many-pie-slices, truncated-y-axis |
 | `clevelandmcgill` | aspect-ratio, too-many-pie-slices, truncated-y-axis |
+| `economistmistakes` | dual-axis-correlation, inverted-y-axis, truncated-y-axis |
 | `howchartslie` | aspect-ratio, dual-axis-correlation, inverted-y-axis, truncated-y-axis |
 
 The citation lists in each entry below are **starting points, not budgets** —
@@ -90,8 +92,10 @@ meeting.
 circle. Fixed = bar chart, one bar per option, each labelled "% of respondents"
 with the base stated. Same counts.
 
-**Citations:** `fewpies`, `datawrapper` (their pie-chart guidance covers when the
-form applies at all), `datatoviz`, `junkcharts`.
+**Citations:** `fewpies`, `datawrapper` — but only for the premise: their
+pie-chart post says "one pie chart can only show one total and its shares," and
+it does *not* separately argue that parts must be mutually exclusive. Don't
+stretch it further than that. Plus `datatoviz`, `junkcharts`.
 
 ### 3. A Pie Chart of Rates or Averages — *Impossible Wholes*, severity 5
 
@@ -113,7 +117,8 @@ their metric is, not a counting mistake.
 same averages, plus the volume behind each one so the weighting is visible.
 
 **Citations:** `fewpies`, `munzner` (part-to-whole is a composition of a whole,
-or it is nothing), `schwabish`, `ftvisvocab`.
+or it is nothing), `datawrapper` (same one-total premise as above), `schwabish`,
+`ftvisvocab`.
 
 ### 4. Group Averages Shown Without the Distribution — *Hiding the Data*, severity 4
 
@@ -149,14 +154,20 @@ position does the work.
 measure against. The rest are guesses."
 
 In a stacked column chart, every segment except the bottom one starts at a
-baseline that moves from column to column, so readers can compare the total and
-the bottom series — and nothing else. The series you actually care about is
-usually floating somewhere in the middle. Datawrapper's guidance is blunt about
-it: bring the most important value to the bottom, because readers can only
-compare values that share a baseline.
+baseline that moves from column to column. Datawrapper puts it plainly: "It's
+hard for readers to compare columns that don't start at the same baseline," and
+their fix is to "bring the most important value to the bottom of the chart."
+
+One correction to how I first framed this, from reading their post: a
+100%-stacked chart has **two** readable baselines, not one — the top edge works
+as well as the bottom. So the sin isn't "only the bottom is readable," it's that
+everything *between* the two baselines floats. Write it that way; adjust the
+poke accordingly.
 
 Ubiquitous in business dashboards, which is what earns it a slot despite the
-milder severity.
+milder severity. The Economist's own rainbow-stack example is a good second
+angle: they stacked a selection of euro-area countries, and stacking implies the
+parts are the whole.
 
 **Charts:** bad = stacked columns with the interesting series stranded in the
 middle. Fixed = the same numbers as small multiples (or the key series pulled
@@ -189,12 +200,15 @@ rediscovering them:
 - **Counts on a choropleth instead of rates** (Cairo's set-piece) — needs
   TopoJSON geometry and a build-time data dependency we don't have yet. Strong
   candidate the moment we take that on.
-- **Rainbow color scales for continuous data** (Wilke, Munzner, and Datawrapper's
-  four-part color-scale series — the best free treatment of this anywhere) —
-  sourcing is not the constraint. What still blocks it is ours: the
-  fixed chart needs a sequential ramp validated on `--chart-canvas` in both
-  themes. Do the palette work first (`dataviz` skill + its validator), then this
-  is ready to write.
+- **Rainbow color scales for continuous data** — blocked on **both** counts,
+  and I had this wrong before. Part 1 of Datawrapper's color series turned out
+  to be a taxonomy that makes no argument against rainbow scales at all, and it
+  explicitly endorses multi-hue sequential gradients (see
+  `docs/sources/datawrapper-color-scales.md`). So we currently have *no*
+  verified source for the rainbow critique — parts 2–4 and Kosara's "How The
+  Rainbow Color Map Misleads" are queued. The palette work is still outstanding
+  too: the fixed chart needs a sequential ramp validated on `--chart-canvas` in
+  both themes. Don't draft this one until a real source is in hand.
 
 ## Conventions reminder
 

docs/source-requests.md

@@ -13,7 +13,7 @@ link here and moves on.
    post say X, and in what words?"
 2. **Human** fetches it and drops the content into `docs/sources/<slug>.md`,
    then points the agent at it. Raw text is fine; so is a paragraph of notes.
-   Whatever's least effort.
+   Whatever's least effort. (PDFs work too — text extracts fine.)
 3. **Agent** uses it as-is or distills it into a citation note, updates the
    relevant sin, and moves the row to *Settled* with what it concluded.
 
@@ -30,41 +30,38 @@ Two standing rules for step 3:
 
 | # | Source | What we need to know |
 | --- | --- | --- |
-| 1 | `blog.datawrapper.de/pie-charts/` — "What to consider when creating pie charts" | Does it state that a pie's parts must be mutually exclusive and sum to a meaningful whole? Exact wording if so. Wanted for backlog entries 2 and 3 (both pie-misuse sins), where the citation note is currently a placeholder. |
-| 2 | `blog.datawrapper.de/dualaxis/` — "Why not to use two axes" | Two things: (a) their original three objections, in their words; (b) the July 2026 update where they revised their position — what changed, and how far. Our dual-axis page cites both halves and I'd rather quote them than characterize them. |
-| 3 | `blog.datawrapper.de/which-color-scale-to-use-in-data-vis/` + the other three parts of the series | What they actually say about rainbow/spectral scales. Needed before writing the rainbow-scale sin (see backlog, "Not yet buildable"). |
-| 4 | The Economist, "Mistakes, we've drawn a few" (Sarah Leo, April 2019) | The **canonical URL**, so the reference can carry a link — it currently ships without one because I couldn't confirm the address. Also: which specific mistakes it owns up to (see claim V1 below). |
-| 5 | Cleveland, McGill & McGill 1988, "The Shape Parameter of a Two-Variable Graph", JASA 83:289–300 | A stable link (JSTOR ID or DOI) for the reference entry, which currently has no URL. |
-| 6 | `blog.datawrapper.de/stacked-column-charts/` | The baseline-comparison passage in their words, for backlog entry 6. Search gave me a paraphrase; I'd like the sentence. |
+| 7 | Isenberg, Bezerianos, Dragicevic & Fekete (2011), *A Study on Dual-Scale Data Charts* | **Venue and DOI.** It's now cited on the dual-axis sin as `isenberg2011` and ships with no `work` and no `url`, because Datawrapper's article names only authors, title and year. |
+| 8 | Stephen Few, *Dual-Scaled Axes in Graphs: Are They Ever the Best Solution?* (Perceptual Edge) | **Year and URL** for `fewdualaxes`, same situation as above. |
+| 9 | Datawrapper color-scale series, **parts 2, 3 and 4** | Whether any of them argues against rainbow/spectral scales. Part 1 does not — see the correction under *Settled*. The rainbow sin has no source until this lands. |
+| 10 | Robert Kosara, *How The Rainbow Color Map Misleads* (eagereyes) | The actual argument, in his words. Currently the only known candidate source for the rainbow sin. |
+| 11 | Robert Kosara, *Understanding Pie Charts* (eagereyes) | URL, and what his experiments actually found. We lean on this to justify not condemning pie charts outright (claim V7). |
+| 12 | The Economist, "Mistakes, we've drawn a few" | **Canonical URL only** — the content arrived and is settled below, but `economistmistakes` still ships without a link. |
 
 ## Claims to verify
 
-These are already **live on the site**. Each rests on recall rather than a
-source I opened this session. None are wild guesses, but they're stated with
-more confidence than I earned, and a wrong attribution costs us more than a
-thinner page would have. Ordered by how much I'd want to check them.
+Live on the site, resting on recall rather than a source anyone opened.
 
 | # | Where | The claim | Confidence |
 | --- | --- | --- | --- |
-| V1 | `truncated-y-axis` → `economistmistakes` | "Several of the mistakes it owns up to are this one" — i.e. that the Economist piece includes truncated-axis examples specifically. | Inference from the article's premise, not from reading it. **Check first.** |
 | V2 | `inverted-y-axis` → `junkcharts` | "Fung has redrawn this exact trick more than once" — that Junk Charts has covered inverted axes repeatedly. | Plausible, unverified. |
 | V3 | `inverted-y-axis` → `vizwtf` | That inverted/flipped axes feature among the specimens there. | Generic, unverified. |
 | V4 | `inverted-y-axis` → `callingbullshit` | That their Misleading Axes module covers inversion, not only truncation and scaling. | Moderate. |
-| V5 | `too-many-pie-slices` → `wilke` | That his proportions chapter shows the same data as pie / stacked bar / side-by-side bars. | High, but it's a specific structural claim. |
+| V5 | `too-many-pie-slices` → `wilke` | That his proportions chapter shows the same data as pie / stacked bar / side-by-side bars. | High, but a specific structural claim. |
 | V6 | `truncated-y-axis` → `wilke` | That his "visualizing amounts" chapter argues bar scales must begin at zero. | High. |
-| V7 | `too-many-pie-slices` → `eagereyes` | That Kosara's pie-chart experiments don't support treating the form as broken by nature. | High — his pie work is well known — but we lean on it to set our stance, so it should be solid. |
+| V7 | `too-many-pie-slices` → `eagereyes` | That Kosara's pie-chart experiments don't support treating the form as broken by nature. | **Upgraded.** Datawrapper's pie post independently describes his *Understanding Pie Charts* as a "great research-based explanation of how people read pie charts," so the work exists and is empirical. What it concludes is still second-hand — see queue row 11. |
 | V8 | `truncated-y-axis` → `huff` | That Huff names it the "gee-whiz graph." | High. |
 | V9 | `aspect-ratio` → `clevelandmcgill` | That slope/direction is among the elementary perceptual tasks ranked in the 1984 paper. | High. |
 
-Verified this session and **not** in need of checking: the Datawrapper dual-axis
-and stacked-column posts exist with the titles cited; the 1988 shape-parameter
-paper is the source of banking-to-45° (the 1984 paper is *not*, which is why
-there are two Cleveland entries in the reference list); eagereyes has a
-banking-to-45° write-up including the "it's about comparing slopes" caveat;
-`viz.wtf` is live.
-
 ## Settled
 
-*(Move rows here with the answer, so we don't re-request them.)*
+| # | Source | Outcome |
+| --- | --- | --- |
+| 1 | Datawrapper, "What to consider when creating pie charts" | Received. Gives us the positive case ("great to show how 100% divide up into a few shares," best at 25/50/75%) *and* the limit ("five max"), both now cited on `too-many-pie-slices`. **But** it does not argue that parts must be mutually exclusive, so backlog entries 2–3 can only lean on "one pie chart can only show one total and its shares." Notes narrowed to match. → `docs/sources/datawrapper-pie-and-stacked.md` |
+| 2 | Datawrapper, "Why not to use two axes" | Received, and it independently draws the line our page drew: of four uses, "only the last… can be used without being potentially misleading, since it only uses the second Y-axis to show an alternative scale and not a second data series" — their example is °F/°C. The July 2026 revision is a narrowing to expert audiences, not a retraction. Yielded two new references. → `docs/sources/datawrapper-dual-axis.md` |
+| 3 | Datawrapper color series, part 1 | Received, and it **refuted my assumption** — a taxonomy, no rainbow argument, and it endorses multi-hue sequential gradients. Backlog corrected. Parts 2–4 re-queued as row 9. → `docs/sources/datawrapper-color-scales.md` |
+| 4 | The Economist, "Mistakes, we've drawn a few" | Content received; URL still wanted (row 12). Settles **V1** — see below. → `docs/sources/economist-mistakes.md` |
+| 6 | Datawrapper, "What to consider when creating stacked column charts" | Received. Verbatim baseline sentence captured, plus a correction: a 100%-stacked chart has *two* readable baselines, not one. Backlog entry 6 rewritten. → `docs/sources/datawrapper-pie-and-stacked.md` |
+| V1 | `truncated-y-axis` → `economistmistakes` | **Confirmed, and corrected.** Truncating the scale is the article's *first* example, so the citation stands — but there is one such example, not the "several" our note claimed. Note rewritten and now quotes her directly. The same article also turned out to contain a dual-axis chart she caught herself on, which is now cited on `dual-axis-correlation`. |
 
-Nothing yet.
+Row 5 (a stable link for Cleveland, McGill & McGill 1988) is still open and has
+moved to no particular priority — the reference reads fine without a URL.

docs/sources/datawrapper-color-scales.md

@@ -0,0 +1,41 @@
+# Datawrapper — "Which color scale to use when visualizing data" (part 1 of 4)
+
+Lisa Charlotte Muth, `blog.datawrapper.de/which-color-scale-to-use-in-data-vis/`,
+**16 March 2021**. Supplied as PDF, read 2026-08-05. Partly answers queue row 3.
+
+## This does not say what I assumed it said
+
+I had queued this expecting it to condemn rainbow/spectral scales, and wrote in
+the backlog that the series was "the best free treatment of this anywhere" for
+that purpose. **Part 1 makes no such argument.** It is a taxonomy — categorical
+vs sequential vs diverging, classed vs unclassed — and its closing section is
+called "It's not as clear-cut as it seems."
+
+Worse for my assumption, it actively softens the single-hue rule:
+
+> You can use only one hue in your sequential gradients (e.g., light blue to
+> dark blue) – but almost all examples I show here use multiple hues (e.g.,
+> light yellow to dark blue). Using two or even more hues increases the color
+> contrast between segments of your gradient, making it easier for readers to
+> distinguish between them.
+
+So "sequential must be one hue" is **not** a rule we can attribute here, and a
+future rainbow sin must not be written as though multi-hue gradients are the
+problem. The problem with rainbow scales is non-monotonic lightness and implied
+banding, which is a different claim needing a different source.
+
+## What it is good for
+
+- Clean definitions of categorical / sequential / diverging, and classed vs
+  unclassed, if a future sin needs to explain the vocabulary.
+- The framing that a color scale is a *mapping* to data, same as any axis.
+- Its own reference list points at Robert Simmon's *Subtleties of Color* (2013)
+  and Wilke's color-scales chapter — both plausible homes for the actual
+  rainbow argument.
+
+## Still needed for the rainbow sin
+
+Parts 2, 3 and 4 of this series, and Kosara's "How The Rainbow Color Map
+Misleads" (referenced by search results, never read). Re-queued. Until one of
+those is in hand, the rainbow sin has **no** verified source and should not be
+drafted.

docs/sources/datawrapper-dual-axis.md

@@ -0,0 +1,70 @@
+# Datawrapper — "Why not to use two axes, and what to use instead"
+
+Lisa Charlotte Muth, `blog.datawrapper.de/dualaxis/`, published **8 May 2018**,
+intro updated **July 2026**. Supplied as PDF, read 2026-08-05.
+Answers queue rows 2 and (partly) 1.
+
+## The July 2026 revision, verbatim
+
+> We originally published this article in May 2018 to explain why you couldn't
+> create dual-axis charts in Datawrapper. Since then, we've changed our minds.
+> We've learned that in some cases, dual-axis charts really are the best way to
+> show the data — and that people who've learned to read them correctly (in
+> financial services, for example) aren't misled by them. […] But all the issues
+> this original article pointed out are still valid. A general audience is
+> indeed likely to misread dual-axis charts.
+
+So: audience-dependent, not a reversal. They now ship the feature on a Business
+plan and kept the article standing. They also link a newer piece, "What to
+consider when creating dual-axis charts" (23 July 2026), not supplied here.
+
+## They draw the same line we drew
+
+The article lists four reasons people reach for dual axes, then says:
+
+> of these four use cases, we think that only the last dual axis chart can be
+> used without being potentially misleading, since it only uses the second
+> Y-axis to show an alternative scale and not a second data series.
+
+The fourth case is **Fahrenheit and Celsius on one series** — the same example
+our sin page arrived at independently. Their test and ours match: the sin is a
+second *data series*, not a second *scale*.
+
+## The three problems
+
+1. **"Zero baselines at different heights can mislead."** The proportions are
+   arbitrary. Their worked example: German vs global GDP looks like it rises at
+   the same rate; extended to zero, global rose 80% and Germany 40%.
+2. **"Even zero baselines at the same height can mislead"** — "humans have a
+   tendency to set things in relation if they're close-by." Readers conclude
+   German GDP exceeded global GDP, then crossed in 2011.
+3. **"They're just hard to read."**
+
+Nutshell line: *"The scales of dual axis charts are arbitrary and can therefore
+(deliberately) mislead readers about the relationship between the two data
+series."*
+
+## The empirical source behind it — worth citing directly
+
+Isenberg, Bezerianos, Dragicevic & Fekete (2011), *A Study on Dual-Scale Data
+Charts*. 15 participants, four chart types; the dual-axis ("superimposed")
+chart was quoted as:
+
+> We found across the board that the superimposed chart performed poorly both
+> in terms of accuracy and time. […] it was ranked lowest by all but one
+> participant. Participants called it very confusing and demanding too much
+> concentration or reflection to decipher the non-monotonic and discontinuous
+> nature of the two scales.
+
+Added to the reference list as `isenberg2011`. Venue/DOI still needed — queued.
+
+Also flagged: Stephen Few, *Dual-Scaled Axes in Graphs: Are They Ever the Best
+Solution?*, which per Datawrapper concludes he "cannot think of a situation that
+warrants them in light of other, better solutions." Added as `fewdualaxes`;
+year and URL queued.
+
+## Alternatives they give
+
+Side-by-side charts; indexed charts (with Knaflic's caveat that this fails when
+one series moves +10000% and the other +5%); prioritise-and-label; connected
+scatterplot. Our page's repentance already recommends the first two.

docs/sources/datawrapper-pie-and-stacked.md

@@ -0,0 +1,71 @@
+# Datawrapper — pie charts, and stacked column charts
+
+Two "Data vis do's & don'ts" posts by Lisa Charlotte Muth, supplied as PDFs and
+read 2026-08-05. Answers queue rows 1 and 6.
+
+## "What to consider when creating pie charts" (3 Jan 2018)
+
+`blog.datawrapper.de/pie-charts/`
+
+Opening line, which is the useful one for us:
+
+> Pie charts are great to show how 100% divide up into a few shares.
+
+And the positive case, which we should keep quoting when people accuse us of
+banning the form:
+
+> Pie charts work best for values around 25%, 50% or 75%. It's easier for
+> readers to spot these percentages in a pie chart than in a stacked bar or
+> column chart.
+
+Then the limits, both of which are our published sin:
+
+> Pie charts are not the best choice if you want readers to compare the size of
+> shares. That's especially true if the differences between the shares are
+> small.
+
+> Pie charts work best if you only have a few values – five max.
+
+Our sample pie has eight. Cited on `too-many-pie-slices`.
+
+**Caveat for backlog entries 2 and 3.** This post does *not* say in so many
+words that a pie's parts must be mutually exclusive and sum to 100% — so it
+can't be cited for the multi-select survey case as I'd hoped. What it does give
+is the premise those sins rest on:
+
+> One pie chart can only show one total and its shares.
+
+That's enough to support "there must be a whole," and nothing more. The backlog
+notes now say exactly that rather than implying a stronger claim.
+
+Also flags Robert Kosara's "Understanding Pie Charts" as a "great research-based
+explanation of how people read pie charts" — independent support for our
+`eagereyes` note (claim V7). URL not captured; queued.
+
+## "What to consider when creating stacked column charts" (13 Feb 2018)
+
+`blog.datawrapper.de/stacked-column-charts/`
+
+The sentence backlog entry 6 is built on:
+
+> It's hard for readers to compare columns that don't start at the same
+> baseline.
+
+And the design guidance:
+
+> Bring the most important value to the bottom of the chart and use color to
+> make it stand out. Your readers can compare values easier with each other if
+> they have the same baseline.
+
+Useful nuance I hadn't accounted for: a 100%-stacked chart has **two** usable
+baselines, not one —
+
+> You will gain a second baseline at the top of your chart where you can place
+> the second most important category in your data.
+
+So the sin is sharper than "only the bottom is readable": everything *between*
+the two baselines floats. Worth writing the page that way.
+
+Also: "Make sure that you include all parts of the total in your charts – and
+only parts of the total." Pairs with the Economist's rainbow-stack example,
+where a partial selection of countries was stacked as if it were the whole.

docs/sources/economist-mistakes.md

@@ -0,0 +1,53 @@
+# The Economist — "Mistakes, we've drawn a few"
+
+Sarah Leo, visual data journalist at The Economist. Supplied as PDF, read
+2026-08-05. Answers queue row 4 (content; the canonical URL is still missing)
+and settles claim **V1**.
+
+Structure: her own archive, grouped into charts that are (1) misleading,
+(2) confusing, (3) failing to make a point, each with a redesign at comparable
+size.
+
+## V1 — confirmed, but our note over-claimed it
+
+The article's **first** example is `Mistake: Truncating the scale` — a bar chart
+of average Facebook likes on posts by the political left:
+
+> The original chart not only downplays the number of Mr Corbyn's likes but also
+> exaggerates those on other posts.
+
+So the sin is there, and it leads the piece. But it is **one** example, not the
+"several" our citation note claimed. Note corrected to match. (She does add
+that "avid followers of this blog will have seen another example of this bad
+practice," which is a pointer elsewhere, not a second case here.)
+
+## Unexpected: it contains our dual-axis sin, self-caught
+
+`Mistake: Forcing a relationship by cherry-picking scales` — dog weights against
+neck sizes, on a dual axis, looking perfectly correlated:
+
+> In the original chart, both scales decrease by three units (from 21 to 18 on
+> the left; from 45 to 42 on the right). In percentage terms, the left scale
+> decreases by 14% while the right goes down by 7%.
+
+Her takeaway is quotable and close to our page's:
+
+> if two series follow each other too closely, it is probably a good idea to
+> have a closer look at the scales.
+
+Added as a citation on `dual-axis-correlation`. A newsroom catching itself doing
+the exact thing is stronger evidence than a textbook saying not to.
+
+## Also useful
+
+- `Taking the "mind-stretch" a little too far` — trade deficit vs manufacturing
+  employment, where "the two data series don't share a common baseline. The
+  baseline of the trade deficit is at the top of the chart." Adjacent to our
+  inverted-axis sin without being a case of it; cite carefully if at all.
+- `Including too much detail` ("What a rainbow!") — stacked areas for ten
+  countries. Her point that "since we are not plotting all euro-area countries
+  it doesn't make any sense to stack the data" is a good detail for the stacked
+  backlog entry: stacking implies the parts are the whole.
+- She cites Francis Gagnon's rule of thumb — leave at least 33% of the plot area
+  free under a line chart that doesn't start at zero. No source captured; not
+  cited anywhere yet.

src/content/sins/dual-axis-correlation.md

@@ -17,8 +17,14 @@ citations:
     note: "Cairo on how aligned axes manufacture relationships that aren’t there."
   - key: swd
     note: "Knaflic’s standing advice: avoid the second axis; separate or index instead."
+  - key: isenberg2011
+    note: "They tested it: the dual-axis (“superimposed”) chart “performed poorly both in terms of accuracy and time” and was “ranked lowest by all but one participant.”"
   - key: datawrapper
-    note: "“Why not to use two axes, and what to use instead” walks through why the two scales' proportions are arbitrary — and they've since published second thoughts, which is worth reading too."
+    note: "“Why not to use two axes” — the scales are arbitrary, so they can “(deliberately) mislead readers about the relationship between the two data series.” Of the four uses they examine, only the alternative-scale one survives. In 2026 they softened the verdict for expert audiences while keeping every objection intact."
+  - key: economistmistakes
+    note: "Filed under “forcing a relationship by cherry-picking scales”: two series fell by three units each, which was −14% on one axis and −7% on the other, and the chart implied a perfect correlation."
+  - key: fewdualaxes
+    note: "Few takes the dual-axis case seriously enough to work through it properly, and still can't find a situation that warrants one."
   - key: truthfulart
     note: "Cairo on what a chart owes its reader, which is the standard this one fails."
 ---
@@ -47,9 +53,16 @@ It isn't automatically dishonest, and this is why the severity here isn't a 5.
 A second axis is legitimate when both axes describe **the same quantity** —
 °C and °F, millimetres and inches, a count and that same count as a share of the
 total. The mapping between the two scales is fixed by arithmetic, so there's
-nothing for you to tune and nothing for the reader to be misled about. Some
-practitioners avoid the second axis even then, as a matter of house style; that
-is a preference, not a rule, and it's not what this page is about.
+nothing for you to tune and nothing for the reader to be misled about.
+
+That's not just our line. Datawrapper examined the four reasons people reach for
+a second axis and concluded that only this one — "an alternative scale and not a
+second data series" — can be used without being potentially misleading. Their
+example is Fahrenheit against Celsius.
+
+Audience matters too: readers trained on these charts, in financial services for
+instance, do read them correctly. If that's genuinely who you're drawing for,
+this page is not about you.
 
 The line is whether *you* picked the alignment. If sliding one scale would
 change the story, you're on the wrong side of it.

src/content/sins/too-many-pie-slices.md

@@ -21,6 +21,8 @@ citations:
     note: "His chapter on proportions puts the same data in a pie, a stacked bar and side-by-side bars, so you can see what each one costs you."
   - key: eagereyes
     note: "Kosara has actually run the experiments, and they don't support treating the pie as broken by nature — useful if someone tells you the chart type itself is the problem."
+  - key: datawrapper
+    note: "Both halves in one place: pies are “great to show how 100% divide up into a few shares” and “work best for values around 25%, 50% or 75%” — but “work best if you only have a few values – five max.”"
   - key: showmenumbers
     note: "Few’s full design manual, for when the short broadside isn’t enough to win the argument."
 ---

src/content/sins/truncated-y-axis.md

@@ -16,7 +16,7 @@ citations:
   - key: wilke
     note: "His chapter on visualizing amounts is blunt: a bar's length is the value, so the scale must begin at zero."
   - key: economistmistakes
-    note: "The Economist reopening its own charts — several of the mistakes it owns up to are this one."
+    note: "The Economist audits its own archive and leads with this exact sin: a bar chart that “not only downplays” one value “but also exaggerates” the others."
   - key: clevelandmcgill
     note: "The perception research: readers compare bar length, so length must map to value from zero."
   - key: tufte

src/lib/references.ts

@@ -147,6 +147,20 @@ export const REFERENCES = {
     kind: 'paper',
     blurb: 'Made aspect ratio measurable: the width-to-height ratio changes how slopes are judged, and “bank to 45°” came from it.',
   },
+  isenberg2011: {
+    authors: 'Petra Isenberg, Anastasia Bezerianos, Pierre Dragicevic & Jean-Daniel Fekete',
+    title: 'A Study on Dual-Scale Data Charts',
+    year: 2011,
+    kind: 'paper',
+    blurb: 'The experiment on dual-axis charts specifically: readers were slower and less accurate with them, and ranked them last.',
+  },
+  fewdualaxes: {
+    authors: 'Stephen Few',
+    title: 'Dual-Scaled Axes in Graphs: Are They Ever the Best Solution?',
+    work: 'Perceptual Edge',
+    kind: 'paper',
+    blurb: 'Works through the dual-axis cases one at a time and concludes none of them survive contact with a better alternative.',
+  },
   schwabish: {
     authors: 'Jonathan Schwabish',
     title: 'Better Data Visualizations',
@@ -182,7 +196,7 @@ export const REFERENCES = {
     work: 'blog.datawrapper.de',
     url: 'https://blog.datawrapper.de/category/datavis-dos-and-donts/',
     kind: 'site',
-    blurb: 'Chart-type-by-chart-type “what to consider” posts, and the clearest free writing anywhere on choosing color scales.',
+    blurb: 'Chart-type-by-chart-type “what to consider” posts, plus a long-running series on color in data visualization.',
     free: true,
   },
   junkcharts: {