Conversation
--html-dir given as a relative path crashed filepath.relative_to(BASE_DIR) (BASE_DIR is absolute), silently producing an empty prices CSV. Resolve the path first and fall back to the raw string. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
- 13-recent-manifest.py: select recent-window snapshots (>=2 quarters, anchored 2024Q3, >=1 snapshot in trailing 12mo), 7 categories. - 14-recent-ipi.py: matched-model index (Jevons elementary per category, review-weighted geometric composite), quarterly + monthly, trailing-12mo headline. - run-recent-pipeline.sh: idempotent driver (download retry -> extract -> build). - gitignore: exclude html-recent/ raw HTML (22GB) and transient .out logs. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
15,150/15,309 snapshots (99%), 100% price extraction across 7 categories. Composite IPI flat over the past year (2025Q1->2026Q1: -0.3%); video -11.6%, coding -6.8%, writing -6.6%, design +2.1%. Includes per-category indices and volume-proxy weights for client-side recompute. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
- code/15-build-site-data.py: reuse step 14's monthly build to emit per-category monthly index -> site/data.json (2.2 KB, trailing 12mo, rebased to window-start=100). - site/index.html + site/ipi.js: category checklist drives live in-browser composite recompute (matches pipeline's exp(Sum w.ln/Sum w)). - Verified: client recompute over all categories reproduces composite_all. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Page wasn't working and the user is building their own site. Removed site/index.html, site/ipi.js, scripts/deploy-site.sh and deleted the gh-pages branch. Kept code/15-build-site-data.py + site/data.json as the data layer for the user's own frontend. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Rebuilt CSRankings-style site now hand-rolls the trend chart and sparklines as inline SVG — no Plotly/CDN. Validated: JS syntax OK, data.json contract complete, client composite reproduces composite_all (headline -2.1% trailing 12mo). Adds deploy-site.sh redeploy helper. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
…ting Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Serve the IPI frontend from /docs (branch mode) instead of the site/ subfolder, which Pages branch mode cannot serve. Drop the Actions workflow; update the data-build script output path. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Self-contained faq.html (no external libs): explains the purpose of the index and documents the exact formulas — price relatives, chained Jevons category index, weighted-geometric-mean composite, headline 12mo change, and review-based weights — with CSS-rendered math. Cross-linked from the main index header. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Polished, still fully self-contained (no external libs/CDN): Inter/system font stack, soft canvas with white rounded cards + subtle shadows, indigo accent, inline-SVG logo + favicon, pill basket toggles, refined table and tooltip, responsive tweaks. FAQ restyled to match (TOC card, paper card, boxed formulas). All JS hooks and the data contract are unchanged. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
…ection - index.html: add full-sentence IPI definition directly beneath the page title - index.html: lay out trend chart (left) and category-selection table (right) side by side via CSS grid, collapsing to stacked below 900px; widen wrap - faq.html: matching aesthetic refresh Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
- ipi.js: significantMoves() flags MoM moves past 0.8% plus the biggest rise/drop; drawChart overlays a green/red segment + labeled % on the composite line, recomputed live as categories are toggled - index.html: legend caption under the chart (green=rise, red=drop) Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
From a user request for a before/after design on the project's headline question. Registered before any outcome is estimated. The move that makes a before/after work here is **staggered arrival**: each niche is dated by the quarter AI listings actually appear in it, not by a platform-wide calendar date. Design 10 died partly because one global date puts every niche's "after" in the same quarters as the pandemic unwind and the 2022 tech contraction; with staggered dates those are absorbed by quarter fixed effects and only the event-time profile is read. Fixed in advance: niches frozen and shared with design 9 so neither design can be accused of picking a definition to suit its result; arrival = AI share >=5% sustained two quarters; controls are **never-treated niches only**, because two-way FE under staggered adoption uses already-treated units as counterfactuals and can return a sign opposite to every underlying effect; SEs clustered on niche; outcomes log price and log review accrual, reported together. Three abandonment points, all pre-outcome: fewer than 100 usable niches (S2), arrivals not actually staggered (S3), and the pre-trend gate G1 — which is the one the question turns on, and the one that killed design 10's image-model result. Endogeneity declared now rather than after: AI sellers enter where AI works, so this can produce an association and never an identified effect. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
…e AI The project had no transaction series on the website and no category split anywhere. Two cards added, plus the paper figure behind them. PLATFORM (step 47). orders = real GMV / real IPI price, the project's only transaction-count series. Drawn as three lines rather than one because the finding is that the quotient falls while the numerator does not: real GMV +11.3% against a real price +35.8%, leaving orders -18.0% vs 2020 and -38.6% from the 2021 peak. Same 2020 = 100 base on all three, so one axis, never two. CATEGORIES (step 62, new). Fiverr publishes no category split, so within-gig review accrual is the only route. Reported as a SERIES for the first time - step 46 estimated the break and never wrote what it broke. Six of seven peak in 2020Q3 and the fall is a simultaneous step between 2021Q2 and 2021Q3, fifteen months before ChatGPT, which itself lands inside a flat stretch where five of seven categories are HIGHER in 2023Q3 than 2022Q3. Identification stated in the script rather than discovered later: within a gig age and calendar quarter move one-for-one, so the shape is identified and the trend is not. The peak quarter is the statistic that survives. A capture-span diagnostic is included for the same reason - mean span widens 1.2 -> 1.75 quarters, so part of the 2024 fall is the crawl. Two structural notes. write_site_block lives in steps 47 and 62 rather than 18, because both series are quotients of the index step 18 builds; step 18 writes data.json whole, so RERUNNING IT DROPS BOTH BLOCKS. And step 34 now takes figure names, so one figure regenerates without figure 4's subsampling curve. The category panel is small multiples, not seven overlaid lines, on a measurement rather than a preference: the site's seven category colours fail a colour-vision check on all 21 pairs, worst pair dE 6.1 deutan and one pair at dE 13.2 for NORMAL vision. Faceting removes the problem at its source. The underlying palette defect still affects the hero price chart and is filed as tech-debt TD2 rather than repainted, since that is a site-wide change. No causal claim anywhere. Both cards say so in their own text, because a chart with a ChatGPT line on it invites exactly that reading. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
From a user correction — "I'm trying to look at just the volume of transactions" — which exposed a real defect in how the page was arranged. Every quantity on the site went through the IPI. That is defensible for the implied order count (Fiverr reports dollars and never an order count, so orders = GMV / price is the only route to one), but it meant the question "what is the volume" was answered with a quotient whose denominator is a price index. Two of the three volume measures in this project never touch a price, and neither was presented as such. The new card is placed FIRST, above the implied-order card, because it is the direct answer and everything below it is derived from something. Pooled review accrual (quarterly, counted off the archived pages) and active buyers (annual, as Fiverr reports it), both indexed 2020 = 100 so they share ONE axis - the mixed cadence is only legitimate because of the shared base, and buyers carries open annual markers so its grain is visible rather than implied. pooled is equal-weighted across the seven categories, not review-weighted: review weight IS the outcome here, so weighting by it would let the largest category set its own denominator. Computed in step 62 rather than in the browser, so the definition lives with the data. The card states what it is not. Accrual is per SURVIVING listing and the archive cannot measure exit (n_404 = 0 across 509,339 captures), so it will not scale to a platform total; buyers counts people, and spend per buyer nearly doubled over the window. An actual count needs the dated order records still unextracted in the archived HTML - encrypted_order_id plus created_at, no price required - which stays PRIORITY 1b. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
The data is 124 GB of flat files with no database, and which tool to reach for changes by tier — pandas for the KB indices and the 4-85 MB price panels, duckdb for the 1.3-5.8 GB cdx intermediates, gzip.open one page at a time for the 86 GB of archived HTML. That is not obvious from the tree, so this is one worked example per tier rather than any analysis. Two things it demonstrates that are easy to miss. The lineage hook: a price row's file_path resolves to the exact .html.gz it was scraped from, which is the check to run whenever a number looks wrong. And the download logs as the cheap index into the HTML store, so the 86 GB never gets globbed. duckdb reads the headerless 1.3 GB gig-month-index.tsv in ~3.5s: 190 months, 201006-202603. Note the parameterised read_csv(columns=$cols) form is silently ignored and then fails on dialect sniffing — the struct is rendered inline instead. Runs top-to-bottom clean under nbconvert --execute; outputs stripped. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
The root was hardcoded to /home/exouser, so the notebook ran on exactly one machine. It is now discovered by walking up for CLAUDE.md + data/, and a preflight cell reports which of the four tiers are actually present. Sections degrade instead of raising. The price panel picks the largest file on hand, falling back from the gitignored balanced-prices.csv (292,447 rows) to the tracked recent-prices.csv (15,150), so a clone gets a real panel. The cdx and HTML sections print what they need and skip; duckdb is an optional import. Verified both ways: full collection machine, 0 errors, all four tiers OK; and a `git archive HEAD` tree — 44 MB, exactly what a clone gets — also 0 errors, with three clean SKIPs. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
… ChatGPT `balanced-prices.csv` is 88 MB and gitignored, so the notebook could not be run from a clone -- `first_present()` fell through to the thin `pilot-prices.csv` without saying so. The panels compress ~11x (88.6 -> 7.9 MB, 25.8 -> 2.9 MB), smaller than `pilot-prices.csv` which was already tracked, so the "exceeds GitHub's limits" reasoning held only for the raw CSV. Commit the gzips, keep the raw files ignored; `pd.read_csv` reads .gz transparently so no analysis code changed. `balanced-gig-category.csv.gz` (0.9 MB) joins them because the category source was a 51 MB manifest also ignored, which would have broken the index and event-study sections on a clone even with prices fixed. code/64 adds the panel builder and a two-way FE event study -- gig effects absorbed by within-gig demeaning, SEs clustered on gig, numpy only so a bare clone can run it. The GEKS index is imported from code/21 unchanged rather than reimplemented, so the notebook plots the papers' estimator. On the 16,128 gigs observed both sides of 2022Q4: the pre-trend is +0.047 log points per quarter (t = 42) and linear to within 0.02 across eleven quarters, nothing breaks at the launch, and the series ends 2024Q4 at -0.213 log points against the extrapolated trend, same sign in all seven categories. The last number is not identified -- no control group, and a linear counterfactual run eight quarters past its data. Held out of the drafts in plans/todo.md until a placebo cut or the step 61 niche design clears it. Verified by cloning the repo and executing the notebook there: 85 s, 0 errors. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01QfFt4d1Q4AkwPAnNCyYgTf
Section 7 was one chart of seven nominal lines. It is now two: the GEKS-Jevons matched-model index over 35 narrow buckets, nominal, and the same index deflated by CPI-U. Both grids share a y-axis, so the gap between them is general inflation. Nothing is reimplemented. code/66-narrow-real-geks.py wires together the estimator (step 21), the narrow taxonomy (step 16) and the deflator (step 23); the notebook imports it. Two results the broad chart could not show. All 35 buckets clear 20/20 quarters at pair_density 1.00, so step 16's thin-subcategory warning was about the recent monthly manifest, not about quarterly matched-model indexing. And deflation -- CPI-U rose 22.3% across the window -- changes no sign: real increases run +3% to +155%. The only two intervals covering zero are Subtitles & Transcribe (+3.1% real) and Translation (+5.5%), the most AI-exposed cell on any crosswalk the project uses. Its own keyword remainder, translation-other, is +51.2%, so the next move is auditing those keywords rather than reading the result. Still no break at the ChatGPT line, at either level, nominal or real. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_016G3pDU1a5BRbp2udySwGXt
…that name themselves
Working-tree files from the preceding sessions, checked in as they stand:
- code/60,61 -- niche construction and the niche-level event study (design 9)
- code/63,63b -- live-recovery calibration and the reach curve behind it
- code/65 -- the event-study figure, plus its PDF/PNG outputs
- data/pilot/niche-{arrival,assignment}.csv, the 2026-08-21 sitemap snapshot
- docs/ipi.js -- volume and transaction charts label which series each peak
belongs to, because accrual, buyers, orders and real GMV peak in different
years and an unqualified "peak" invited the wrong reading
One fix on the way in: the new real-GMV label referenced an undefined C_GMV,
which would have thrown on every render of the transactions chart. It is
TX_COLORS.gmv_real, the colour the series is already drawn in.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_016G3pDU1a5BRbp2udySwGXt
A user looked at the fine-grained chart and said the coding line looked suspiciously high. It is high, and the reason is worth more than the chart. Two diagnostics in code/66-narrow-real-geks.py, both reusing step 21's walk: geks_variant() swaps the bilateral aggregator (median-of-logs in place of the mean Jevons is defined as), floor_shares() reports the cheap end. A cell in §7 runs them. The plotted index is unchanged. Coding's matched 2020Q1->2024Q4 log changes are 0.00 / 0.69 / 2.07 at the 20th/50th/90th: the typical matched gig exactly doubled, the top decile went eight-fold, and Jevons averages logs, so the plotted +145% sits far above the median-of-logs +74%. It is not outlier contamination -- 1% trimming moves it 0.5 index points. And the level is frame-dependent: the same estimator ranks coding first here and fourth on the panel frame the site publishes, where audio leads. The explanation that looks obvious fails, and is recorded as failing. Listings entering at or below $10 reprice 2-3x faster per observed quarter than dearer ones in every family, so the retiring $5 floor lifts every line -- but it does not order them: translation is the most floor-heavy family (64.5% at or below $5 in 2020) and the flattest series on the chart. Opened as findings.test.md R11 (FAIL): the draft reports the mean-of-logs level on one frame and says the category table is not a ranking. R9 promises that; this is the evidence, and it is stronger than the overlapping intervals given now. Untouched by all three checks: the within-family ordering and the nominal/real gap, including flat translation. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_016G3pDU1a5BRbp2udySwGXt
A second author appended a composite pre-trend analysis to the notebook, edited against the pre-section-7 version. GitHub's resolution dropped the deflated chart and left the new cells calling geks_df, a name section 7 no longer defines. Kept both sides. The real chart and the robustness cell are back; the new cells are section 9, verbatim, under a heading saying what the design is and that section 8 runs the same test with gig fixed effects and clustered SEs. geks_df is aliased to nom_b in the section 7 build cell so their code needs no edit, and their statsmodels cell is guarded, since statsmodels is not a project dependency and this notebook has to run on a bare clone. 39 cells, 0 errors, 7 figures, statsmodels absent. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_016G3pDU1a5BRbp2udySwGXt
…ises A user asked why marketing looked so high. It is high, +211% nominal and +172% real at the broad level, and unlike coding it survives every check. Marketing's listings are the shortest-lived on the panel -- median 9 quarters between first and last capture against design's 33 -- so entry composition was the obvious suspect. It is not: restricting to gigs spanning 8+ quarters moves marketing 210.79 -> 210.69, and no other domain by more than 0.2 index points, though 30 of 190 bilaterals change. That test is now a column in section 7's check cell, because it generalises to any category a reader gets suspicious of. The rest of the battery agrees. No single gig is worth more than 5% of the Ads & PPC level under a leave-one-out; the bilaterals are well populated (median 61 matched gigs per quarter pair, minimum 10); and marketing reads +282% on the published panel frame, higher than here, where coding's rank collapses from first to fourth. So the two suspicious categories have different diagnoses and only coding's is a measurement artefact. What marketing has is width. Email & Funnels reads 373 at 2024Q2 against 321 and 318 either side, 95% band [284, 491]. The spike is inside the noise. Also opened: section 6 asserts entrants price above incumbents, citing step 57. Step 57's finding was about AI-labelled entrants. On this panel the general claim inverts -- marketing entrants list at $15 against incumbents' $30 at 2023Q1 -- so the sentence needs restating or re-deriving. Verified: 39 cells, 0 errors. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_016G3pDU1a5BRbp2udySwGXt
Second merge with the same author, from the same stale base, dropping the same work: section 7's real chart, the check cell, the section 9 heading and the geks_df alias. Kept her newest cells verbatim except for two fixes -- the notebook as pushed carries both errors in its own committed outputs. NameError: geks_df, in cells 32 and 34. Section 7 renamed that table when it went to 35 categories. geks_df = nom_b is aliased in the section 7 build cell so her code reads the broad nominal table under its old name and needs no edit. KeyError: pre_fitted_index, in the section 8 plot. pre and post are copies taken before the fitted columns are added to g, so those columns do not exist on them. Now g.loc[pre.index, ...] and g.loc[post.index, ...], which is what the code intends. Structural fix, not exercised here: statsmodels is absent on this machine and the guarded cell skips. 39 cells, 0 errors, 7 figures. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_016G3pDU1a5BRbp2udySwGXt
Both section 7 charts have been in the file since 4ba13c6, but every output was stripped, so opening the notebook showed code and no images. That is the repo convention and it is the wrong one for a notebook whose point is two charts you are meant to compare. Committed with outputs: 7 figures, 0 errors. Section 7 cell 24 is the nominal chart, cell 25 is the same index deflated by CPI-U on the same y-axis. 1.4 MB. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_016G3pDU1a5BRbp2udySwGXt
…unning it §10 fits ln(real price) on the gig fixed effect (task value), quarter effects, reputation and AI exposure, over 169,337 gig-quarter observations. It imports code/76-price-model.py rather than restating it — build_panel, design, fe_ols, qdummies, mde and load_slug_exposure — so the notebook and runs/price-model/model.md are one fit. Every printed number reproduces the script's to the digit. What it establishes: reputation, +7.33% real price per doubling of cumulative reviews (t 26), an independent replication of steps 22/27 in 2020Q1 dollars; and task value, SD 1.249 log points, seven times the spread of everything time-varying put together, which is the argument for keeping it a fixed effect rather than a proxy. What it does not: Exposure x Post is -0.0333 (t -1.35) against an MDE of 0.0689, so the null rules nothing out — a silence, not a zero — and gate A fails anyway. The new event-study chart is the clearest statement the project has of why: the exposure gap opens across 2021, a year before ChatGPT exists, and is flat for the whole post-period. §10.5 carries the false positive that was caught, +13.76% per 10pp collapsing to +0.73% under one linear trend per category. Two of §10's dependencies were untracked, so a clone could not run it: step 76 itself, and runs/ai-slug-diffusion/diffusion.md, which §10.5 reads as its regressor. Both committed. Step 76 also gained a .csv.gz fallback for PRICES and path arguments to build_panel, since the 88 MB CSV is gitignored and only the 7.9 MB gzip is in the repo; its own output is byte-identical after the change. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_017CZzqPanjxFvPfB9TXK6se
§10 put task value in a gig fixed effect, which is the honest home for it and also a dead end: a fixed effect that ABSORBS task value can never REPORT it. `a_i` came back with an SD of 1.249 log points and no way to say what any part of it was. Worse, a gig fixed effect also absorbs the permanent part of reputation, so §10 could only ever watch one listing reprice itself and was structurally blind to the comparison the reputation question is about. Two new steps replace the gig anchor with a task anchor. `77-task-taxonomy.py` builds a two-level taxonomy. Domains are step 04's; subcategories are matched on the DELIVERABLE PHRASE stripped out of the title (`<seller>: I will <X> for $N on fiverr.com`, 99.99% coverage and far richer than the slug). Rules are ORDERED and first-match-wins, most specific first, so `shopify dropshipping store` reaches `ecommerce` before `web_dev` sees `store`; the order is part of the definition. 65 nodes, 77.5% of gigs named, nodes under 30 gigs folded into `<domain>/other`. Reference task value runs $6.66 (translation/subtitling) to $59.38 (marketing/content_strategy), a spread of 2.188 log points. Domain explains 5.7% of ln(real price), the node 10.9%, the gig 91.4% — the taxonomy roughly doubles what seven domains name and is still nowhere near the fixed effect. `78-reputation-price.py` fits reputation at three levels. Between nodes +6.94% per doubling; between gigs within a node -9.08% (t -28); within a gig +7.62% (t 31). B and C have OPPOSITE SIGNS, both precisely estimated on 270,965 observations. Step 25 saw this at category level as "near zero versus positive"; holding the task fixed at node level turns the cross-section significantly negative. A high review count marks two things at once — a seller who has been around, which raises price, and one running a cheap high-volume operation, which lowers it. Between sellers the second dominates; within one listing only the first can move. Neither number may be quoted without the other. Per-node slopes are positive in all 58 estimated nodes, 45 significant, +1.84% (translation/localization) to +27.11% (translation/interpreting). Commodity translation sits at the bottom, consultative work at the top. Notebook §11 (15 cells, four charts) imports both steps rather than restating them, the convention §10 uses for step 76; every printed number reproduces `runs/taxonomy/*.md`. The chart that carries the argument plots one node twice — one point per listing (slope -0.038), then each listing centred on its own mean (+0.091). The reversal is visible without a regression. Two corrections made while wiring it up. Step 77 was reporting reference values on the full panel while step 78 fit on rows carrying both reputation columns, so the project briefly held two different reference task values — marketing/content_strategy was $67.11 in one and $59.38 in the other; step 77 now computes on the estimation sample and says so. And §11.3's scatter was captioned as showing the reversal "before any regression", which is false: `adjusted` comes from the fit containing b1, so the gap is approximately b1 x (node mean log reviews - grand mean), measured correlation 0.978. The caption now states this and credits the sign to spec B. Open, both in todo: the taxonomy has no hand-labelled validation, and `translation/voiceover_leak` (721 gigs) shows step 04's classifier leak sits inside the nodes rather than repaired by them. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01TftqfBPLvNdb4GJYdSKXXe
The incoming commit replaced §7's chart colours with an explicit Okabe-Ito `DOMAIN_COLORS` map for the seven domains. §11 had landed with its own seven-colour palette, so a domain would have been one colour in §7 and another in §11's three charts. §11 now aliases `DOMAIN_COLORS` instead of defining a competing map, and its figures are re-executed against it. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01TftqfBPLvNdb4GJYdSKXXe
… approximates "Price increases 7.7% when review counts double within one gig" was a coefficient with no picture and two unasked questions behind it. §11.4a asks both. IS IT A STRAIGHT LINE? The left panel is a Frisch-Waugh partial-residual plot: gig, quarter and rating are swept out of the price AND out of the review count, so the plotted line's slope is spec C by construction — the cell asserts the FWL slope equals bC to 1e-9 — and the only thing free to move is the shape. Fourteen equal-count bins, gig-clustered 95% CIs. The answer is mostly, not exactly. A quadratic in ln(1+reviews) is -0.00277 (t -2.51), so strict log-linearity is REJECTED. The departure is small and monotone: +8.14% per doubling at 10 reviews, +7.23% at 100, +6.29% at 1,000, +5.63% at 5,000, against the pooled +7.62%. The median gig-quarter carries 111 reviews (p90 965), so the linear coefficient is a fair summary over the mass — but it is now stated as an approximation rather than a functional form, and the concavity is visible in the top bin without the parametric test. WHAT DOES THE RATE BUY? +7.6% per doubling is a rate, not an outcome, and it pays only if listings accumulate doublings. Most do not: the median listing travels 1.53 doublings over its whole observed life, p90 4.63, and 38% never manage even one. At spec C's slope the median listing's entire review history is worth +11.9% in real price. A secondary top axis converts doublings to implied gain directly. The cells reuse §11.4's y / X / igig / bC rather than refitting, so the section still holds one spec C. Outputs are executed and embedded, per the convention that committed charts are visible without running the notebook. Two reading hazards handled rather than left: the x-axis is doublings, not log points, so the coefficient is legible off the chart; and the histogram's last bar is a clipped 6+ tail (3.0% of listings), labelled so it is not misread as a mode. Logged as U6 (the instruction) and R12 (the functional-form critique, now answered) in tests/findings.test.md. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01UzPM6JZMKR7bpHE5XciSU7
…r's sitemaps taken Two steps, tested against the live sites rather than the archive. FIVERR GIG PAGES ARE HARD-BLOCKED, MEASURED NOT ASSUMED. 15 gig pages, 3s apart, honest browser UA: 15/15 HTTP 403. Retried with complete standard browser headers: still 403. The homepage 403s on the first request, so it is not a rate limit. The body is a PerimeterX CAPTCHA wall. Passing it would need CAPTCHA-solving, proxy rotation or fingerprint spoofing — circumvention of an access control, refused. This closes todo PRIORITY 0b: its question (1), the paginated reviews endpoint, cannot be tested at all because no HTML is served, so the archive back-fill is dead by the plan's own abandonment criteria. 80-fiverr-sitemap-census.py RECOVERS WHAT WAS RECORDED AS IMPOSSIBLE. Step 39 found n_404 = 0 across 509,339 Wayback captures — the archive stops re-requesting a delisted URL rather than recording its death, so exit was unmeasurable. Fiverr publishes its live inventory as sitemaps, listed in its own robots.txt and served WITHOUT the PerimeterX wall. Eight requests give 291,068 live gig URLs and put 12,720 of the panel's 39,933 gigs (31.9%) still listed. Survival by year of last panel observation runs 2.2% (2018) to 55.0% (2024). That is an exit hazard, and it bears on §4.4's survivorship gap and on the objection that the index is computed on survivors. Two limits are in the docstring, not the commit only: absence means NOT LISTED, a lower bound — a gig may be paused, unindexed or rotated out rather than dead; and no sitemap carries a price, so this cannot extend the index. 79-mercor-board.py NEEDS NO CRAWLER. work.mercor.com/jobs server-renders every open listing into __NEXT_DATA__, so one GET is the whole cross-section — nothing to rate-limit. robots.txt allows /jobs/; /apply/, /api/ and /interview/ are untouched. 394 listings, 100% rate coverage, median hourly band $70-$100, plus capacity fields the archived copies lack (remainingSlots, 11,418 open slots; suppliedSlots; recentCandidatesCount; hoursPerWeek; postedAt). Stated in the docstring before anyone reaches for it: Mercor listings are employer-posted HOURLY RATE BANDS for contract roles, not seller-posted fixed prices for deliverables. Not comparable to Fiverr gig prices, and not to be spliced into the IPI. Today's file is a cross-section; the panel accrues only by re-running, where the version field separates a genuine reprice from a re-crawl. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01UzPM6JZMKR7bpHE5XciSU7
…res on the table The panel's right edge is starved -- design falls 7,093 -> 320 matched gigs per adjacent quarter pair between 2024Q3->Q4 and 2025Q4->2026Q1. This separates the collapse into two causes with very different remedies. Irreducible: 38% of 2025+ fiverr.com captures are HTTP 403 and only 19% are 200. The PerimeterX wall step 80 measured against live gig pages was already turning the Wayback crawler away through 2025. A 403 capture has a digest and a length, so a naive census counts it as supply; its body is a CAPTCHA page and carries no price, so step 81 drops them rather than doubling 2025-2026 supply on paper for nothing. Ours, and larger than expected: 34,807 gig-days for 2025+ were indexed in March and never downloaded, against 8,363 that were, because the balanced and expanded manifests quota over seven domains and drop `uncategorized`. Collecting them roughly doubles matched-pair supply in every 2025-2026 quarter -- and still leaves ~1,200 matched gigs across all categories against a 1,200-per-category target. Third pool: Wayback ingests late. Re-querying prefix `q` returns 252 gig-shaped 200s in 2025+ against the 212 the March pull saw (+19%), with 36 of the new records in 2026Q2-Q3, which the old index does not cover at all. - 01: the window is now an argument (--from/--to/--out/--prefixes). The refresh goes to raw-2025/, not raw/ -- raw/ is the provenance record for every number already in the draft, and step 81 unions the two at read time. - 81: separates the three pools, emits a step-08 manifest (35,030 captures). - run-refresh-2025-pipeline.sh: waits out the CDX pull, then 81 -> 08 -> 09. Prices land in a new file; the pilot paper is mid-submission and nothing here may move a published figure. Downloads never run while the pull is live -- both hit web.archive.org, and probing the CDX API during it already produced 429s. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01KL94gcTBgrhyruuRtutA5Y
Serialising the two bought nothing. 35,030 of the ~35k manifest captures come from the March 2026 all-time pull and do not depend on the refresh at all -- the refresh only adds a further ~0.5-19% -- so waiting hours for it before fetching anything cost time for no data. The download runs at --concurrency 6 --max-rate 6 instead of 10/10, which leaves headroom for the CDX pull; measured 300 captures/min with 471/473 HTTP 200 and no 429s on either job. Two correctness fixes the new ordering requires: - 81 writes the manifest atomically (temp + rename). Step 08 loads its manifest once at startup, so a rename swaps safely under a live pass, and the next pass picks up the larger set. A plain open(..., "w") would let pass 1 read a half-written manifest. - The driver waits for the in-flight download to exit before starting pass 2. Two step-08 processes appending to one checkpoint would interleave and corrupt the resume set. Premise verified before committing to the fetch: three manifest captures parsed end-to-end. 2025-01 and 2026-07 captures are real gig pages carrying packageList prices with no px-captcha wall; one 2025-12 capture returned 200 with no price block, so 35,030 is an upper bound on extraction yield rather than a forecast. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01KL94gcTBgrhyruuRtutA5Y
…hausted anyway The overnight pipeline landed 35,938 pages and 35,925 price rows at 100.0% extraction. Step 82 replaces yesterday's projection with the realised number, measured on collected prices rather than on index supply. The projected level was right; the projected gain was not. All-category matched pairs at 2025Q1->Q2 go 1,093 -> 1,285 against a projected 702 -> 1,286 -- the after correct to one gig, the before understated by ~390 already on disk. So 1.12x, not the 1.83x the to-do carried. The seven published domains move 34,164 -> 34,433 (1.01x) and nothing in the draft moves. The reason is the finding. 22,947 of 24,345 (94.3%) of the refresh's gigs are priced in exactly one quarter and only 884 carry an adjacent pair; a bilateral needs two visits, so a one-shot capture is worth nothing however cleanly it extracts. Not collection loss either -- the manifest holds only 893 such gigs, so 99.0% of the recoverable pairs were recovered. Newly measured, and the sharper half: the archive's adjacent-quarter revisit rate is flat at 74-82% across 2018-2024, then 44.1% (2025) and 34.5% (2026). Supply is the product of gigs-captured and revisit-rate, so the right edge loses twice over. The 403 wall was only the first column. Decided: the recovered supply changes the error bars, not the index window. Design's best 2025-2026 pair is 337 against a 1,200 target. Ten new families become differenceable at all but none reach 30 in any pair -- existence, not measurement. Also commits steps 67-75 and their run notes, which the to-do already cites but which had never been tracked. The 11 GB of refresh HTML and the 35,925-row panel are gitignored; re-querying CDX is still worth it for 2026Q2-Q3, which the March pull never covered. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01ArSV92b617GAi1AEY2kZ67
Closes the leftover "re-query CDX for 2026Q2-Q3" with a negative on two
archives, and builds the only route that remains.
Wayback stopped crawling Fiverr after 2026Q1. A fresh pull of prefix z over
20250101 -> 20260907 -- the first look past 2026-03 this project has had --
gives 459/212/393/207/173 captures for 2025Q1..2026Q1 and then 11 and 10 for
2026Q2-Q3, one of them a 200. 403s do not rise, so the captures simply stop.
Common Crawl, never previously tried, is closed too: fiverr.com/* returns one
index block in Aug 2026, Aug 2025 and Aug 2024 alike, and its only status-200
records are robots.txt. Recorded so neither archive is re-tried.
Wayback additionally began refusing connections from this host mid-run
(Connection refused, its only A record) while archive.org answered 200. The
26-prefix refresh was stopped rather than left retrying; checkpoints are intact
and it resumes with one command. It is still worth finishing for 2025, where 14
prefixes were never pulled, and not for 2026.
That leaves live gig pages, which steps 63/63b had already validated on stored
HTML: no price selection in late-fetched pages (+0 USD, CI [+0, +0]) and
displayed orders at median lag 2 months, so a page opened in 2026-09 is mostly a
window onto 2026Q2-Q3 -- at the cost of survivorship, since only 26.2% of the
panel is still listed and skewed rich.
83 stratified target list: category x panel review-count quartile,
round-robin under one seed, so ANY prefix of the list is balanced and an
operator who stops early holds a sample rather than a head.
84 paste-in browser collector: same-origin in the operator's own session,
one request per 4-9s, keeps the two JSON blobs (~12 KB) rather than the
1.3 MB page, and halts on three consecutive 403s. No CAPTCHA solving,
proxy rotation or fingerprint spoofing -- refused 2026-09-04, still
refused. Fiverr's robots.txt permits gig pages and advertises them.
85 ingest: panel rows plus realised-order rows, and a report that always
prints the three stacked selections -- survivorship, relevancy-ranked
display, and price bucketing ("$50-$100" is not an amount).
Pilot-before-scale applied to the tooling itself: the chain was dry-run on 60
stored pages before anyone spent a browser session, which caught the reviews
slice matching an inner object (2 bytes for a gig with 368 reviews) and title
taking the package name instead of the gig's og:title.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01163NZVFu7VFmWtZjpUabdT
The operator saw a 429 on web.archive.org, which resolved an ambiguity this host could not: IA is up and rate-limiting us after yesterday's ~11 GB pull. The refresh is paused on its checkpoints, not dead. That prompted a recount which overturns part of the earlier note. The claim that "the captures simply stop" and "403s do not rise" came off prefix z alone -- half of one small prefix, 1,465 records. Recounted on the 79,853 records from the 12 prefixes pulled a day earlier: quarter captures 403 share 200s distinct gig pages 2025Q4 12,601 1.0% 2,239 940 2026Q1 9,734 18.1% 1,180 563 2026Q2 1,204 89.3% 9 1 2026Q3 1,209 59.1% 152 50 So the wall IS the mechanism, quarter by quarter, and 2026Q3 holds ~50 distinct gig captures in a 14.5% partial pull -- order 350-500 archive-wide, worth collecting, against the "essentially none" claimed before. The conclusion survives its own arithmetic being wrong: 2026Q2 holds one gig-shaped 200 against 2026Q3's 50, so adjacent-quarter matched pairs are ~0 either side and the archives are still no route to a 2026 index. The live-page plan stands unchanged. One new signal: 2026Q3 recovers (403 89.3% -> 59.1%, 200s 9 -> 152), the first non-monotone quarter since the wall began, which makes a later re-query worth more than this one. Pacing in step 01 is now configurable (--min-interval, --concurrency) and the global default slowed 0.75s -> 1.5s. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01163NZVFu7VFmWtZjpUabdT
…t hides them
The wall blocks new fetches. It does not touch the 86 GB already downloaded, and
step 59 had established that a gig page embeds review records dated by ORDER
date carrying what the buyer paid. Nothing after step 09 had read them at scale.
Step 86 scans all 397,698 stored captures, dedupes on encrypted_order_id keeping
the earliest capture that showed each order, and recovers 681,668 distinct
orders. 2025 -- the year the listed-price panel loses -- is thick: 10,236 /
7,360 / 7,233 / 6,602 orders per quarter over 2,250-4,479 gigs. 2026 is
independently confirmed dead, 23 orders across Q2-Q3, because these records come
from captures and the captures stopped.
The obvious analysis would have produced a spectacular false finding. Bucket
shares straight off the published field show sub-$50 orders going from ~0% of
the market in 2022-23 to ~54% in 2025 -- a collapse in what buyers pay, arriving
right on the AI timeline. It is an artefact twice over:
* sub-$50 orders carried NO price bucket before ~2024Q2 -- in 2022Q3, 46% of
orders are unpriced and the cheapest bucket that exists is $50-$100, while
by 2024Q3 missingness is ~0 and $0-$50 alone is 50%. The apparent <$50 share
tracks coverage almost exactly.
* the labels changed at the same moment: $5-$20 and $20-$50 vanish, $0-$50
appears, so bins on published labels straddle a break.
Step 87 conditions on $50+, where the boundaries 50/100/200/400/800 hold across
every era. There the series is flat: median bin $100-200 in all 17 quarters from
2022Q1 to 2026Q1, drifting $50-100 +4.8pp, $100-200 -3.6pp, $200-400 -2.5pp,
$400-800 -0.4pp, $800+ +1.6pp. A mild hollowing of the middle, not a decline.
The cost is stated rather than hidden: the series says nothing about the sub-$50
segment, which is roughly half of all orders and unmeasurable before 2024. And
it is not the IPI -- different price object, no chaining.
The 118 MB order panel is gitignored and regenerable; the distilled quarterly
series and both reports are tracked.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01163NZVFu7VFmWtZjpUabdT
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