{ "schema_version": "1.0", "name": "Four Day For AI", "url": "https://4day4ai.org/evidence.json", "movement_url": "https://4day4ai.org/movement.json", "readable_url": "https://4day4ai.org/case-files", "language": "en", "updated": "2026-10-31", "date_timezone": "America/Los_Angeles", "collection_type": "curated_project_case_file", "coverage": "A growing selection of relevant evidence, not a systematic review or an exhaustive account of the literature.", "verified_meaning": "The recorded claims, scope and citations have been checked against the listed sources. Verified does not mean independently replicated or universally applicable.", "public_statuses": [ "verified" ], "interpretation": [ "Empirical findings describe the studied tasks, workers, places and periods; the movement's demand is a separate policy position.", "Task productivity, economy-wide productivity, hourly compensation and worker well-being are different measures.", "The evidence does not support a universal tenfold productivity claim or a claim that every workplace can already move to 32 hours at unchanged weekly pay.", "A source's publication date, data period and the project's verification date are recorded separately." ], "entries": [ { "schema_version": "1.0", "id": "cruces-2026-ai-education-gaps", "status": "verified", "claim_type": "empirical", "topic": "ai_productivity", "updated": "2026-10-31", "period": "September–November 2025", "primary_source_id": "cruces-fernandez-meijide-galiani-galvez-lombardi-2026", "summary": { "finding": "In a randomized online experiment with 1,174 Argentine adults, AI assistance improved scores on a short business problem-solving task and narrowed the gap between higher- and lower-education participants.", "scope": "Participants were aged 25–45, and the study measured performance on one task outside a workplace, not wages, employer productivity or long-term learning." }, "population": { "description": "Low- and high-education adults aged 25–45 in Argentina.", "geographies": [ "Argentina" ], "samples": [ { "group": "Participants", "n": 1174, "unit": "adults" } ] }, "method": { "design": "randomized_controlled_trial", "description": "Online randomized experiment outside firms; participants completed an incentivized workplace-style business problem-solving task with or without an embedded GPT-4.1 assistant, followed by a non-AI-assisted module.", "intervention": "An embedded GPT-4.1 assistant available during the main task.", "comparator": "The same task completed without AI assistance." }, "results": [ { "id": "low-education-score-gain", "measure": "Overall task score gain for low-education participants", "value": 1.242, "unit": "standard_deviations", "basis": "Scores are standardized using the low-education control group's mean and standard deviation.", "source_ids": [ "cruces-fernandez-meijide-galiani-galvez-lombardi-2026" ] }, { "id": "high-education-score-gain", "measure": "Overall task score gain for high-education participants", "value": 0.834, "unit": "standard_deviations", "basis": "Scores are standardized using the low-education control group's mean and standard deviation.", "source_ids": [ "cruces-fernandez-meijide-galiani-galvez-lombardi-2026" ] }, { "id": "education-gap-without-ai", "measure": "High-education minus low-education task score gap without AI", "value": 0.548, "unit": "standard_deviations", "basis": "Control group without AI assistance.", "source_ids": [ "cruces-fernandez-meijide-galiani-galvez-lombardi-2026" ] }, { "id": "education-gap-with-ai", "measure": "High-education minus low-education task score gap with AI", "value": 0.139, "unit": "standard_deviations", "basis": "AI-assisted group; the authors report this closes 75% of the baseline gap.", "source_ids": [ "cruces-fernandez-meijide-galiani-galvez-lombardi-2026" ] }, { "id": "follow-up-low-education", "measure": "Follow-up score gain without AI for low-education participants", "value": 0.171, "unit": "standard_deviations", "basis": "Non-AI-assisted follow-up module; the high-education estimate was smaller and statistically insignificant.", "source_ids": [ "cruces-fernandez-meijide-galiani-galvez-lombardi-2026" ] } ], "limitations": [ "Online experiment outside firms; one roughly 20-minute business problem-solving task, not a workplace or a full job.", "Participants were 1,174 adults aged 25–45 in Argentina; results may not generalize to other countries or age groups.", "Short-term outcomes; the follow-up measures short-run unassisted performance, not durable skill formation.", "The assistant was GPT-4.1; results may not generalize to other tools or tasks.", "Task scores are standardized and rubric-graded, not wages or employer productivity." ], "relevance": { "supports": "AI can raise task performance and reduce education-related performance gaps in a short online task.", "does_not_establish": [ "Workplace productivity or earnings gains", "That AI reduces inequality economy-wide", "Shorter working weeks", "Unchanged weekly pay" ] }, "sources": [ { "id": "cruces-fernandez-meijide-galiani-galvez-lombardi-2026", "title": "Does Generative AI Narrow Education-Based Productivity Gaps? Evidence from a Randomized Experiment", "publisher": "National Bureau of Economic Research", "authors": [ "Guillermo Cruces", "Diego Fernández Meijide", "Sebastian Galiani", "Ramiro H. Gálvez", "María Lombardi" ], "url": "https://www.nber.org/papers/w34851", "doi": "10.3386/w34851", "full_text_url": "https://www.nber.org/system/files/working_papers/w34851/w34851.pdf", "published": "2026-02-01", "updated": "2026-10-01", "source_type": "working_paper", "primary": true, "accessed": "2026-10-31", "checked_sections": [ "Abstract", "Introduction", "Section 2 Experimental design", "Section 2.1 Recruitment strategy" ] } ], "verification": { "verified_on": "2026-10-31", "method": "primary_source_check", "checked_source_ids": [ "cruces-fernandez-meijide-galiani-galvez-lombardi-2026" ], "replicated": false, "notes": "Read the NBER abstract and introduction. NBER lists issue February 2026 and revision October 2026; exact days are not stated, so month-start dates are recorded." } }, { "schema_version": "1.0", "id": "cui-2026-copilot-field-experiments", "status": "verified", "claim_type": "empirical", "topic": "ai_productivity", "updated": "2026-10-31", "period": "September 2022–December 2023; three experiments lasted 2–8 months", "primary_source_id": "cui-demirer-jaffe-musolff-peng-salz-2026", "summary": { "finding": "Across three randomized workplace experiments involving 4,867 software developers, researchers estimated that GitHub Copilot use increased weekly completed tasks by about 26%.", "scope": "Results varied across the three large employers, and the estimate concerns use of the tool rather than access alone; the study did not measure code quality, pay or working hours." }, "population": { "description": "Software developers at Microsoft (primarily the United States), Accenture offices in Southeast Asia, and an anonymous Fortune 100 electronics company.", "geographies": [ "United States", "Southeast Asia", "Not reported for the anonymous company" ], "samples": [ { "group": "Pooled analysis sample", "n": 4867, "unit": "developers" }, { "group": "Microsoft experiment", "n": 1746, "unit": "developers" }, { "group": "Accenture experiment", "n": 320, "unit": "developers" }, { "group": "Anonymous company experiment", "n": 3054, "unit": "developers" } ] }, "method": { "design": "randomized_controlled_trial", "description": "Three field experiments run by the companies; random access to GitHub Copilot; treatment assignment instrumented for actual use; outcomes from company telemetry.", "intervention": "GitHub Copilot, an AI coding assistant providing code completions and suggestions.", "comparator": "Developers not assigned access to Copilot during the experiment." }, "results": [ { "id": "completed-tasks", "measure": "Weekly completed tasks among Copilot users", "value": 26.08, "unit": "percent_relative_increase", "basis": "Instrumental-variable estimate pooling the three experiments; standard error 10.3%.", "source_ids": [ "cui-demirer-jaffe-musolff-peng-salz-2026" ] }, { "id": "code-commits", "measure": "Code updates (commits)", "value": 13.55, "unit": "percent_relative_increase", "basis": "Secondary outcome; standard error 10.0%.", "source_ids": [ "cui-demirer-jaffe-musolff-peng-salz-2026" ] }, { "id": "code-compiles", "measure": "Code compilation events", "value": 38.38, "unit": "percent_relative_increase", "basis": "Secondary outcome; standard error 12.55%.", "source_ids": [ "cui-demirer-jaffe-musolff-peng-salz-2026" ] } ], "limitations": [ "Each experiment was noisy and estimates varied; the pooled 26.08% estimate relies on an instrumental-variable model of use.", "Take-up and duration varied: Microsoft's control group gained access early, Accenture had only a few hundred developers, and the anonymous company's staggered rollout was short.", "Outcomes are completed tasks, commits and builds; the study does not measure code quality, wages, hours or employment.", "Three large employers that chose to run Copilot experiments; not a representative sample of developers or firms.", "The three experiment counts sum to 5,120 developers, while the pooled analysis sample is 4,867.", "Less experienced developers had higher adoption and larger estimated gains; the paper reports significant gains for recent hires and junior developers but not for longer-tenured or more senior developers." ], "relevance": { "supports": "Randomized field evidence that generative AI can raise measured developer output at large employers.", "does_not_establish": [ "Economy-wide productivity gains", "That every developer or team benefits", "Shorter working weeks", "Unchanged weekly pay" ] }, "sources": [ { "id": "cui-demirer-jaffe-musolff-peng-salz-2026", "title": "The Effects of Generative AI on High-Skilled Work: Evidence from Three Field Experiments with Software Developers", "publisher": "Management Science", "authors": [ "Kevin Zheyuan Cui", "Mert Demirer", "Sonia Jaffe", "Leon Musolff", "Sida Peng", "Tobias Salz" ], "url": "https://pubsonline.informs.org/doi/10.1287/mnsc.2025.00535", "doi": "10.1287/mnsc.2025.00535", "full_text_url": "https://economics.mit.edu/sites/default/files/inline-files/draft_copilot_experiments.pdf", "published": "2026-02-27", "source_type": "peer_reviewed_article", "primary": true, "accessed": "2026-10-31", "checked_sections": [ "Abstract (final article, via Crossref metadata)", "Working paper abstract", "Introduction", "Section 2.2 Experiments" ] } ], "verification": { "verified_on": "2026-10-31", "method": "primary_source_check", "checked_source_ids": [ "cui-demirer-jaffe-musolff-peng-salz-2026" ], "replicated": false, "notes": "The Management Science page was blocked by Cloudflare. Checked the final article's abstract via Crossref metadata (4,867 developers; 26.08%, SE 10.3%) and the authors' February 2025 working-paper full text for design and estimates. The final abstract repeats the working-paper headline estimate." } }, { "schema_version": "1.0", "id": "deputy-2025-frontline-ai-consultation", "status": "verified", "claim_type": "empirical", "topic": "worker_voice", "updated": "2026-10-31", "period": "Survey fielded August 21–September 11, 2025", "primary_source_id": "deputy-workplace-intelligence-2025", "summary": { "finding": "In a survey of 1,500 frontline shift workers in the US, UK and Australia, 15% said they were always consulted before new AI tools were introduced, while 42% said they were rarely or never consulted.", "scope": "The vendor-commissioned online survey covered hospitality, foodservice, retail and healthcare; responses were self-reported and may not represent all workers." }, "population": { "description": "Hourly shift workers in hospitality, foodservice, retail and healthcare across three countries.", "geographies": [ "United States", "United Kingdom", "Australia" ], "samples": [ { "group": "Survey respondents", "n": 1500, "unit": "workers" } ] }, "method": { "design": "cross_country_survey", "description": "Online panel survey conducted by Walr for Deputy and Workplace Intelligence; 1,500 completed responses from an online panel.", "intervention": "None; observational survey.", "comparator": "None; descriptive percentages." }, "results": [ { "id": "always-consulted", "measure": "Workers saying they are always consulted before new AI solutions are implemented", "value": 15, "unit": "percent_of_workers", "basis": "The report states: 'Only 15% of workers are always consulted before new AI solutions are implemented.'", "source_ids": [ "deputy-workplace-intelligence-2025" ] }, { "id": "sometimes-consulted", "measure": "Workers saying they are sometimes consulted", "value": 35, "unit": "percent_of_workers", "basis": "Chart category 'Sometimes consulted'.", "source_ids": [ "deputy-workplace-intelligence-2025" ] }, { "id": "rarely-never-consulted", "measure": "Workers saying they are rarely or never consulted", "value": 42, "unit": "percent_of_workers", "basis": "Chart category 'Rarely/Never consulted'.", "source_ids": [ "deputy-workplace-intelligence-2025" ] }, { "id": "consultation-dont-know", "measure": "Workers saying they do not know how often they are consulted", "value": 9, "unit": "percent_of_workers", "basis": "Chart category 'Don't know'. Consultation categories sum to 101% because of rounding.", "source_ids": [ "deputy-workplace-intelligence-2025" ] }, { "id": "employer-transparency", "measure": "Workers saying their employer is completely transparent about AI's impact on jobs", "value": 17, "unit": "percent_of_workers", "basis": "Report: 'Only 17% of workers say their employer is completely transparent about AI's impact on jobs.'", "source_ids": [ "deputy-workplace-intelligence-2025" ] } ], "limitations": [ "Employer-commissioned survey by a workforce-management vendor; not an independent academic or official statistical survey.", "Online panel of 1,500 hourly workers in four industries and three countries; not a probability sample of all workers.", "The report states a margin of error of plus or minus 0.8 percentage points at 95% confidence, which is implausibly small for a sample of 1,500 (a simple random sample implies roughly 2.5 points); the precision of the estimates is therefore uncertain.", "The report does not print the exact questionnaire wording; it reports the item as 'Always consulted before new AI solutions are implemented'.", "Self-reported perceptions; the study did not verify employers' actual consultation practices.", "Descriptive only; it cannot establish effects of consultation on productivity, retention or well-being." ], "relevance": { "supports": "Most surveyed frontline workers said they were not always consulted before AI rollouts.", "does_not_establish": [ "That all workers lack consultation", "That consultation causes better outcomes", "AI productivity effects", "Shorter working weeks or unchanged weekly pay" ] }, "sources": [ { "id": "deputy-workplace-intelligence-2025", "title": "Better Together: How AI and Human Connection Will Transform Frontline Work", "publisher": "Deputy", "authors": [ "Deputy", "Workplace Intelligence" ], "url": "https://cdn.assets.prezly.com/c06a36ef-1efa-4e09-b763-0bc442de6894/-/inline/no/Better%20Together_%20How%20AI%20and%20Human%20Connection%20Will%20Transform%20Frontline%20Work%20(2025%20Report).pdf", "published": "2025-11-11", "source_type": "employer_commissioned_survey", "primary": true, "accessed": "2026-10-31", "checked_sections": [ "Introduction", "Key findings", "Consultation chart", "Methodology" ] } ], "verification": { "verified_on": "2026-10-31", "method": "primary_source_check", "checked_source_ids": [ "deputy-workplace-intelligence-2025" ], "replicated": false, "notes": "Read the report's introduction, consultation chart, key findings and methodology. The press release is dated 2025-11-11 and the report is copyright 2025. The survey was conducted by Walr between August 21 and September 11, 2025. The report does not publish the exact question wording, so the record preserves its reported item wording and flags that limitation." } }, { "schema_version": "1.0", "id": "dillon-2025-ai-work-patterns", "status": "verified", "claim_type": "empirical", "topic": "ai_working_time", "updated": "2026-10-31", "period": "September 2023–October 2024; six-month experiment", "primary_source_id": "dillon-jaffe-immorlica-stanton-2025", "summary": { "finding": "In a six-month experiment involving 7,137 knowledge workers at 66 large firms, Microsoft 365 Copilot access cut Outlook email time by 1.4 hours per week and after-hours app use by 15 minutes per week.", "scope": "The randomized study detected no change in the number of email threads, meetings or documents; it measured activity in Microsoft applications, not output quality or overall productivity." }, "population": { "description": "Knowledge workers at 66 large firms that used Microsoft Office applications; 3,684 workers were randomly assigned to treatment.", "geographies": [ "Multinational firms; countries not reported" ], "samples": [ { "group": "Participating workers", "n": 7137, "unit": "workers" }, { "group": "Treated workers", "n": 3684, "unit": "workers" }, { "group": "Participating firms", "n": 66, "unit": "firms" } ] }, "method": { "design": "randomized_controlled_trial", "description": "Firms randomly assigned eligible workers to Copilot access or control for six months; telemetry measured time and activity in Microsoft 365 applications.", "intervention": "Microsoft 365 Copilot access, integrated into Outlook, Teams, Word and other Office applications.", "comparator": "Workers who continued with existing tools; the control group maintained for six months." }, "results": [ { "id": "outlook-time-itt", "measure": "Time using Outlook for email, intention-to-treat", "value": -1.4, "unit": "hours_per_week_change", "basis": "Intention-to-treat estimate; a 12% reduction relative to the pre-period mean.", "source_ids": [ "dillon-jaffe-immorlica-stanton-2025" ] }, { "id": "outlook-time-late", "measure": "Time using Outlook for email, local average treatment effect", "value": -2, "unit": "hours_per_week_change", "basis": "Local average treatment effect for Copilot users, instrumenting use with treatment assignment; a 17% reduction.", "source_ids": [ "dillon-jaffe-immorlica-stanton-2025" ] }, { "id": "after-hours-app-time", "measure": "Time in digital applications outside regular working hours", "value": -0.25, "unit": "hours_per_week_change", "basis": "A 9% reduction; the authors interpret this as some saved time returning to workers.", "source_ids": [ "dillon-jaffe-immorlica-stanton-2025" ] }, { "id": "task-quantities", "measure": "Number of email threads, Teams meetings and Word documents", "value": "no detected change", "unit": "reported_direction", "basis": "Treated and control workers replied to the same number of email threads, attended the same number of Teams meetings and completed the same number of Word documents.", "source_ids": [ "dillon-jaffe-immorlica-stanton-2025" ] } ], "limitations": [ "Telemetry covers Microsoft 365 applications, not output quality, firm productivity or compensation.", "Workers were not required to use Copilot; weekly use stabilized just under 40% of treated workers, so the study reports intention-to-treat and local average treatment effects.", "Participating firms were large, multinational and early adopters; workers may not be representative.", "The study detects time savings and reduced after-hours work, not changes in task quantity or composition.", "The AEA version is forthcoming; the checked full text is the accepted manuscript, and the NBER working paper was revised in November 2025." ], "relevance": { "supports": "AI can save time on specific knowledge-work tasks and reduce after-hours work in large firms.", "does_not_establish": [ "Higher output or firm productivity", "Shorter working weeks", "Unchanged weekly pay", "That saved time is spent on additional work or leisure" ] }, "sources": [ { "id": "dillon-jaffe-immorlica-stanton-2025", "title": "Shifting Work Patterns with Generative AI", "publisher": "National Bureau of Economic Research", "authors": [ "Eleanor Wiske Dillon", "Sonia Jaffe", "Nicole Immorlica", "Christopher T. Stanton" ], "url": "https://www.nber.org/papers/w33795", "doi": "10.3386/w33795", "full_text_url": "https://www.aeaweb.org/content/file?id=24562", "published": "2025-05-01", "updated": "2025-11-01", "source_type": "working_paper", "primary": true, "accessed": "2026-10-31", "checked_sections": [ "Abstract (NBER and AEA accepted manuscript)", "Introduction", "Section I.A Experimental Design", "Section I.B Adoption", "Results discussion" ] } ], "verification": { "verified_on": "2026-10-31", "method": "primary_source_check", "checked_source_ids": [ "dillon-jaffe-immorlica-stanton-2025" ], "replicated": false, "notes": "Read the NBER abstract and the AEA accepted-manuscript PDF in full. NBER lists issue May 2025 and revision November 2025; exact days are not stated, so month-start dates are recorded. The AEA version is forthcoming at AER: Insights." } }, { "schema_version": "1.0", "id": "epi-productivity-pay-2026-09", "status": "verified", "claim_type": "empirical", "topic": "productivity_distribution", "updated": "2026-10-31", "period": "1979 Q4 to 2026 Q2", "primary_source_id": "epi-productivity-pay-tracker", "summary": { "finding": "US net productivity grew 93.7%; typical workers' hourly compensation grew 32.7% from 1979 Q4 to 2026 Q2.", "scope": "These are inflation-adjusted US series: compensation includes wages and benefits for private-sector production and nonsupervisory workers, while productivity covers the total economy." }, "population": { "description": "US total economy and private-sector production/nonsupervisory workers", "geographies": [ "United States" ], "samples": [] }, "method": { "design": "descriptive_time_series", "description": "EPI compares cumulative growth using BLS and BEA data and a common consumer-price deflator.", "intervention": "None; historical comparison.", "comparator": "Each series' 1979 Q4 baseline." }, "results": [ { "id": "net-productivity-growth", "measure": "Net output per hour", "value": 93.7, "unit": "percent_cumulative_growth", "basis": "1979 Q4–2026 Q2; output net of depreciation.", "source_ids": [ "epi-productivity-pay-tracker" ] }, { "id": "typical-compensation-growth", "measure": "Typical workers' hourly compensation", "value": 32.7, "unit": "percent_cumulative_growth", "basis": "1979 Q4–2026 Q2; average wages plus benefits for the covered group.", "source_ids": [ "epi-productivity-pay-tracker" ] } ], "limitations": [ "Compensation is not median wages or the pay of every worker.", "The two series cover different populations.", "This historical comparison does not identify an AI effect; data may be revised." ], "relevance": { "supports": "Productivity and typical compensation can grow at different rates.", "does_not_establish": [ "AI caused this gap", "A 32-hour week's costs", "Trends outside the United States" ] }, "sources": [ { "id": "epi-productivity-pay-tracker", "title": "The Productivity–Pay Gap", "publisher": "Economic Policy Institute", "authors": [ "Economic Policy Institute" ], "url": "https://www.epi.org/productivity-pay-gap/", "updated": "2026-09-14", "source_type": "institutional_data_analysis", "primary": true, "accessed": "2026-10-31", "checked_sections": [ "Page update date", "Productivity–Pay Tracker", "Chart notes and source", "Pay definition", "Methodology and data sources" ] } ], "verification": { "verified_on": "2026-10-31", "method": "primary_source_check", "checked_source_ids": [ "epi-productivity-pay-tracker" ], "replicated": false, "notes": "Recorded the displayed tracker snapshot; did not independently reproduce the underlying series." } }, { "schema_version": "1.0", "id": "france-1998-35-hour-week", "status": "verified", "claim_type": "empirical", "topic": "working_time", "updated": "2026-10-31", "period": "1998-2002 reform rollout; core analysis sample 1994-2001, with a 2003 extension", "primary_source_id": "carry-et-al-2026", "summary": { "finding": "An analysis of France's 1998–2002 shift from 39 to 35 hours with pay preserved estimated that payroll tax cuts offset job losses from the hours cut, leaving employment largely unchanged; total factor productivity rose about 2% and output fell about 1%.", "scope": "This working paper studies firms around a size-based legal threshold, and its results concern the combined reforms, not a 32-hour week or AI." }, "population": { "description": "Private-sector firms in mainland France and their employees, centered on firms with 10-18 or 22-48 employees in 1997 to exploit the 20-employee mandate threshold; matched administrative employer-employee and balance-sheet data.", "geographies": [ "France" ], "samples": [ { "group": "Firm-year observations in the main balanced panel (1994-2001)", "n": 117048, "unit": "firm-year observations" }, { "group": "Labor Force Survey households per year", "n": 75000, "unit": "households" }, { "group": "Workers in the 2001 working-time supplement", "n": 14000, "unit": "workers" }, { "group": "Full-time workers in the 1999 DARES RTT survey", "n": 1618, "unit": "workers" } ] }, "method": { "design": "quasi_experimental_staggered_difference_in_differences", "description": "Exploits the size-based rollout of the 35-hour mandate (firms over 20 employees from January 2000, smaller firms from January 2002) and differential exposure to the hours cut and payroll tax cut; combines matched employer-employee registers covering private-sector jobs, firm balance sheets, and worker surveys.", "intervention": "Statutory workweek cut from 39 to 35 hours with monthly pay preserved, bundled with employer payroll tax cuts.", "comparator": "Firms below the 20-employee threshold before the mandate and firms with different exposure to the two components; no randomization." }, "results": [ { "id": "employment-package", "measure": "Employment effect of the reform package", "value": "unchanged", "unit": "reported_direction", "basis": "The abstract and conclusion state that the reform package left employment unchanged; the zero masks offsetting effects.", "source_ids": [ "carry-et-al-2026" ] }, { "id": "employment-hours-only", "measure": "Employment effect of the hours cut absent the payroll tax cuts", "value": -3.8, "unit": "percent_change", "basis": "Counterfactual estimate: absent the tax cuts, the shorter workweek would have reduced employment by 3.8%.", "source_ids": [ "carry-et-al-2026" ] }, { "id": "total-factor-productivity", "measure": "Total factor productivity", "value": 2, "unit": "percent_change", "basis": "TFP rose 2% after accounting for changes in workforce composition.", "source_ids": [ "carry-et-al-2026" ] }, { "id": "output", "measure": "Value added", "value": -1, "unit": "percent_change", "basis": "Value added fell 1% while total hours worked fell 6%.", "source_ids": [ "carry-et-al-2026" ] }, { "id": "hours", "measure": "Total hours worked in the firm", "value": -6, "unit": "percent_change", "basis": "The mandate reduced total hours worked in the firm by 6%.", "source_ids": [ "carry-et-al-2026" ] }, { "id": "adoption", "measure": "Adoption of the 35-hour week among mandated firms", "value": 45, "unit": "percentage_points", "basis": "Adoption rose 45 percentage points among mandated firms; 86% of mandate-induced adopting firms claimed the payroll tax cut.", "source_ids": [ "carry-et-al-2026" ] }, { "id": "hourly-wage", "measure": "Hourly wages", "value": 2, "unit": "percent_change", "basis": "Hourly wages rose 2%, less than the 6% hours reduction; hourly labor costs rose by less than 1%.", "source_ids": [ "carry-et-al-2026" ] }, { "id": "long-run-employment", "measure": "Employment three to four years after adoption", "value": -3, "unit": "percent_change", "basis": "Adopting the 35-hour week reduced employment by 3% three to four years later, significant at the 10% level, partly after adoption-contingent subsidies were removed.", "source_ids": [ "carry-et-al-2026" ] } ], "limitations": [ "Working paper; not peer reviewed.", "The reform bundled the hours cut with payroll tax cuts, so the employment-neutral package does not identify the effect of shorter hours alone.", "Estimates are local average treatment effects for firms induced to adopt by the size-based mandate.", "Core estimates cover 1994-2001, with a 2003 extension; longer-run effects are less precisely estimated.", "Effects were skill-biased: employment rose for managers and high-skill professionals and fell for other employees.", "Worker surveys are descriptive and condition on continued employment.", "The reform was to 35 hours, not 32, and was not financed by AI." ], "relevance": { "supports": "A national pay-preserving hours reduction can be paired with productivity gains and roughly neutral aggregate employment, but the employment result depended on large offsetting payroll tax cuts and the gains were unevenly distributed.", "does_not_establish": [ "AI financed the reduction", "Universal feasibility", "A uniform 32-hour schedule", "That shorter hours alone preserve employment or pay for themselves", "That all workers benefit; effects were skill-biased", "That the French institutional setting generalizes to other countries" ] }, "sources": [ { "id": "carry-et-al-2026", "title": "The Effects of a Shorter Workweek on Employment, Output, and Productivity", "publisher": "National Bureau of Economic Research", "authors": [ "Pauline Carry", "Claire Montialoux", "Elio Nimier-David", "Alexandra Roulet", "Nina Roussille" ], "url": "https://www.nber.org/papers/w35917", "doi": "10.3386/w35917", "full_text_url": "https://www.nber.org/system/files/working_papers/w35917/revisions/w35917.rev0.pdf", "updated": "2026-10-16", "source_type": "working_paper", "primary": true, "accessed": "2026-10-31", "checked_sections": [ "Abstract", "Introduction", "Data", "Sample and variable definitions", "Results", "Mechanisms", "Conclusion" ] } ], "verification": { "verified_on": "2026-10-31", "method": "primary_source_check", "checked_source_ids": [ "carry-et-al-2026" ], "replicated": false, "notes": "Read the 117-page NBER Working Paper 35917 revision PDF dated 16 October 2026, including the abstract, data and sample, results, mechanisms, and conclusion. The paper is a working paper, not peer reviewed. No independent replication." } }, { "schema_version": "1.0", "id": "germany-2026-four-day-week-follow-up", "status": "verified", "claim_type": "empirical", "topic": "working_time", "updated": "2026-10-31", "period": "Six-month pilot beginning in early 2024; follow-up survey as of February 2026", "primary_source_id": "intraprenor-munster-2026", "summary": { "finding": "Two years after a German pilot, 70% of 40 responding organizations still used reduced hours (including 22% of all respondents who had adapted their model), while 30% had stopped.", "scope": "Continuing organizations reported work-life benefits, while those that stopped reported transition costs; these are self-reported perceptions, not evidence of causal effects or audited productivity gains." }, "population": { "description": "German organizations that began a six-month four-day-week pilot in 2024 and their employees.", "geographies": [ "Germany" ], "samples": [ { "group": "Organizations starting the 2024 pilot", "n": 45, "unit": "organizations" }, { "group": "Organizations completing the pilot", "n": 41, "unit": "organizations" }, { "group": "Organizations in the February 2026 follow-up", "n": 40, "unit": "organizations" }, { "group": "Employees in the follow-up survey", "n": 167, "unit": "employees" } ] }, "method": { "design": "nonrandomized_follow_up_survey", "description": "Follow-up organizational survey in February 2026, about two years after the 2024 six-month pilot; 40 of 41 completing organizations responded. A separate employee follow-up surveyed 167 people in current-WTR, former-WTR, and control groups. Comparisons are cross-sectional and self-reported.", "intervention": "A four-day week or other work time reduction with full pay during the 2024 pilot.", "comparator": "Organizations that discontinued work time reduction and employees who never transitioned; no randomization." }, "results": [ { "id": "organizations-followed", "measure": "Organizations in the follow-up survey", "value": 40, "unit": "organizations", "basis": "40 of the 41 organizations that completed the original six-month pilot participated in the February 2026 follow-up.", "source_ids": [ "intraprenor-munster-2026" ] }, { "id": "continuing-work-time-reduction", "measure": "Organizations still operating some form of work time reduction", "value": 70, "unit": "percent", "basis": "28 of 40 responding organizations operated some form of work time reduction as of February 2026.", "source_ids": [ "intraprenor-munster-2026" ] }, { "id": "discontinued-work-time-reduction", "measure": "Organizations no longer operating work time reduction", "value": 30, "unit": "percent", "basis": "12 of 40 responding organizations no longer operated work time reduction as of February 2026.", "source_ids": [ "intraprenor-munster-2026" ] }, { "id": "adapted-model", "measure": "Organizations that adapted their work time model", "value": 22, "unit": "percent", "basis": "22% of the 40 organizations had adapted their model since the end of the trial; the most cited reason was that the original four-day format was too rigid for everyday operations.", "source_ids": [ "intraprenor-munster-2026" ] }, { "id": "employer-attractiveness", "measure": "Continuing organizations reporting improved employer attractiveness", "value": 75, "unit": "percent", "basis": "Among continuing organizations, 44% reported improvement and 31% much improvement (75% total); 25% reported no change.", "source_ids": [ "intraprenor-munster-2026" ] }, { "id": "work-life-balance", "measure": "Continuing organizations reporting improved work-life balance", "value": 94, "unit": "percent", "basis": "Among continuing organizations, 69% reported improvement and 25% much improvement (94% total); 6% reported no change.", "source_ids": [ "intraprenor-munster-2026" ] }, { "id": "employee-burnout", "measure": "Mean self-reported burnout score", "value": 2.43, "unit": "mean_score", "basis": "Current work-time-reduction group mean was 2.43, former group 2.68, and control group 3.19; current versus control p < .001. 167 respondents; cross-sectional follow-up; the report describes the current group as reporting lower burnout than the control group.", "source_ids": [ "intraprenor-munster-2026" ] }, { "id": "employee-stress", "measure": "Mean self-reported work stress score", "value": 2.91, "unit": "mean_score", "basis": "Current work-time-reduction group mean was 2.91, former group 3.20, and control group 3.35; current versus control p < .05.", "source_ids": [ "intraprenor-munster-2026" ] } ], "limitations": [ "Follow-up survey, not a randomized trial; 40 of 41 organizations responded, and 30% had discontinued.", "Employee outcomes are cross-sectional and self-reported; the control group was not randomly assigned.", "Organizations that discontinued may differ systematically from those that continued.", "The report measures perceptions, not audited productivity or financial outcomes.", "The original pilot lasted six months; the two-year follow-up captures survival, not long-term causal effects.", "Models varied across organizations; this was not a uniform 32-hour week." ], "relevance": { "supports": "Most responding German organizations sustained some form of reduced hours two years after the pilot, but a substantial minority discontinued; continuation was associated with perceived benefits, while organizations that reversed cited transition costs and a worsening of working conditions after returning to a standard schedule.", "does_not_establish": [ "AI financed the reduction", "Universal feasibility", "A uniform 32-hour schedule", "That reduced hours caused the reported organizational or employee outcomes", "That discontinued organizations failed because of the hours reduction rather than other operational factors", "That employee-group differences are causal" ] }, "sources": [ { "id": "intraprenor-munster-2026", "title": "The 4-Day-Week in Germany: A Follow-Up Two Years After the Start of the Trial", "publisher": "Intraprenör and University of Münster", "authors": [ "Julia Backmann", "Felix Hoch", "Johannes Hüby", "Marika Platz", "Matthias Sinnemann" ], "url": "https://www.wiwi.uni-muenster.de/tow/sites/tow/files/downloads/4DW_FollowUp_Report_Englisch.pdf", "published": "2026-02-19", "source_type": "research_report", "primary": true, "accessed": "2026-10-31", "checked_sections": [ "Study context and introduction", "Organizational results at a glance", "Development of working time models until 2026", "Work time reduction from the employee perspective", "Conclusion" ] } ], "verification": { "verified_on": "2026-10-31", "method": "primary_source_check", "checked_source_ids": [ "intraprenor-munster-2026" ], "replicated": false, "notes": "Read the 18-page Intraprenör/University of Münster follow-up report PDF and extracted the organizational results and employee-perspective sections. The 19 February 2026 release date was confirmed on the study project page. The follow-up is a cross-sectional survey, not a randomized trial. No independent replication." } }, { "schema_version": "1.0", "id": "iceland-2015-2019-shorter-week", "status": "verified", "claim_type": "empirical", "topic": "working_time", "updated": "2026-10-31", "period": "2015-2019 trials; contracts negotiated 2019-2021; report published June 2021", "primary_source_id": "alda-autonomy-2021", "summary": { "finding": "Iceland's 2015–2019 public-sector trials cut many participants' weeks from 40 to 35–36 hours without pay cuts, and the report says productivity and services were maintained or improved in most workplaces.", "scope": "The trials covered over 2,500 workers in more than 100 workplaces, had no control group, and did not test a 32-hour week; some later reductions required extra staffing costs." }, "population": { "description": "Public-sector employees in Reykjavík City and Icelandic Government workplaces, including nine-to-five and shift workers in offices, playschools, social services, and hospitals.", "geographies": [ "Iceland" ], "samples": [ { "group": "Trial workers", "n": 2500, "unit": "workers" }, { "group": "Trial workplaces", "n": 100, "unit": "workplaces" }, { "group": "Public-sector trials", "n": 2, "unit": "trials" } ] }, "method": { "design": "nonrandomized_public_sector_trial", "description": "Two large-scale trials initiated in 2015 and 2017; mixed quantitative workplace output indicators, staff surveys, and qualitative interviews; comparisons with prior years and internal targets; no randomized control group.", "intervention": "Reduction from a 40-hour week to 35 or 36 hours with no reduction in pay; schedules varied by workplace.", "comparator": "Workplace-level prior-year data and internal targets; no control group." }, "results": [ { "id": "trial-workers", "measure": "Workers covered by the trials", "value": 2500, "unit": "workers", "basis": "The report says the trials involved over 2,500 workers, more than 1% of Iceland's working population, across more than 100 workplaces.", "source_ids": [ "alda-autonomy-2021" ] }, { "id": "weekly-hours", "measure": "Full-time weekly hours after the trials", "value": "35-36", "unit": "hours_per_week", "basis": "Many participants moved from a 40-hour to a 35- or 36-hour working week; this was not a uniform 32-hour week.", "source_ids": [ "alda-autonomy-2021" ] }, { "id": "productivity-and-service", "measure": "Productivity and service provision", "value": "maintained or improved", "unit": "reported_direction", "basis": "The report says productivity and service provision remained the same or improved across the majority of trial workplaces, based on workplace administrative indicators and interviews; there was no control group.", "source_ids": [ "alda-autonomy-2021" ] }, { "id": "contract-coverage", "measure": "Working population covered by shorter-hours contracts or negotiation rights", "value": 86, "unit": "percent_of_working_population", "basis": "About 170,200 union members covered by contracts out of a 197,000 working population; either moved to shorter hours or gained a mechanism to negotiate them. The report dates this to its completion in June 2021, not 2022.", "source_ids": [ "alda-autonomy-2021" ] }, { "id": "government-cost", "measure": "Estimated additional Icelandic Government cost from added staffing", "value": 4.2, "unit": "billion_ISK_per_year", "basis": "The report estimates total additional Icelandic Government costs at 4.2 billion ISK yearly (24.2 million GBP, 33.6 million USD), with about two-thirds in healthcare. Not all post-trial reductions were cost-free.", "source_ids": [ "alda-autonomy-2021" ] } ], "limitations": [ "Public-sector trials only; workplaces applied and volunteered, and the sample is not representative of the private sector.", "No randomization or control group; before/during comparisons cannot isolate the effect of shorter hours.", "Output indicators vary by workplace; some statistics were excluded because they lacked a suitable pre-period or came from self-selected samples.", "Wellbeing outcomes are self-reported, and the report was published by advocacy organizations (Alda and Autonomy).", "The 86% figure is a June 2021 count of contractual coverage or entitlement (170,200 of 197,000 working population), not proof that all covered workers actually work shorter hours; it is not a 2022 estimate.", "Not all post-trial reductions were cost-free; the government estimated 4.2 billion ISK yearly in added healthcare staffing costs.", "The trials reduced hours to 35-36, not a uniform 32-hour week." ], "relevance": { "supports": "Large public-sector trials reduced hours without pay cuts while most participating workplaces maintained or improved service and output indicators, and subsequent contracts extended shorter-hour entitlements or negotiation mechanisms to most of the Icelandic workforce.", "does_not_establish": [ "AI financed the reduction", "Universal feasibility", "A uniform 32-hour schedule", "That the trials caused the productivity or wellbeing improvements", "That all 86% actually work shorter hours rather than holding a contractual right or mechanism", "That the 86% figure is a 2022 estimate; the report dates it to June 2021" ] }, "sources": [ { "id": "alda-autonomy-2021", "title": "Going Public: Iceland's Journey to a Shorter Working Week", "publisher": "Alda and Autonomy", "authors": [ "Guðmundur D. Haraldsson", "Jack Kellam" ], "url": "https://autonomy.work/wp-content/uploads/2021/06/ICELAND_4DW.pdf", "published": "2021-06-01", "source_type": "research_report", "primary": true, "accessed": "2026-10-31", "checked_sections": [ "Executive summary", "How were service provision and productivity affected?", "After the trials: continuing the path to shorter working hours", "Appendix II: Maintaining service", "Appendix IV: Challenges" ] } ], "verification": { "verified_on": "2026-10-31", "method": "primary_source_check", "checked_source_ids": [ "alda-autonomy-2021" ], "replicated": false, "notes": "Read the 82-page Alda/Autonomy report PDF downloaded from Autonomy and extracted the executive summary, service/productivity section, post-trial contracts, Appendix II, and Appendix IV. The 86% coverage figure is dated June 2021 in the report (170,200 of 197,000 working population), not 2022; it counts contractual coverage or entitlement, not realized shorter hours for every worker. No independent replication." } }, { "schema_version": "1.0", "id": "ilo-2024-wage-productivity-gap", "status": "verified", "claim_type": "empirical", "topic": "productivity_distribution", "updated": "2026-10-31", "period": "1999–2024", "primary_source_id": "ilo-gwr-2024-25", "summary": { "finding": "Across 52 high-income countries, average labour productivity grew 29% from 1999 to 2024, while average real wages grew 15%.", "scope": "These population-weighted figures compare GDP per worker with inflation-adjusted average wages, not typical workers' pay; 2024 uses first-half data, and most of the gap opened before 2007." }, "population": { "description": "52 high-income countries, combined into population-weighted average indices of labour productivity and real wages.", "geographies": [ "52 high-income countries" ], "samples": [] }, "method": { "design": "observational_series", "description": "The ILO builds two indices with 1999 as the base year (1999 = 100), weighted by countries' populations: labour productivity measured as GDP per worker (IMF data) and average real wages (ILO wage estimates, CPI-deflated, with wage employment from ILOSTAT). The 2024 values use the first and second quarters of the year.", "intervention": "Not applicable; no policy or programme was evaluated.", "comparator": "The real wage index versus the labour productivity index over the same period, and the size of the gap across two sub-periods (1999–2006 versus later years)." }, "results": [ { "id": "productivity-growth-1999-2024", "measure": "Labour productivity (GDP per worker)", "value": 29, "unit": "percent_cumulative_growth", "basis": "1999–2024; population-weighted average across 52 high-income countries; index base 1999=100; 2024 based on Q1–Q2; value as published, rounded to the nearest percentage point.", "source_ids": [ "ilo-gwr-2024-25" ] }, { "id": "real-wage-growth-1999-2024", "measure": "Average real wage (CPI-deflated)", "value": 15, "unit": "percent_cumulative_growth", "basis": "1999–2024; population-weighted average across 52 high-income countries; index base 1999=100; 2024 based on Q1–Q2; value as published, rounded to the nearest percentage point.", "source_ids": [ "ilo-gwr-2024-25" ] }, { "id": "productivity-wage-gap-1999-2024", "measure": "Cumulative productivity growth minus cumulative real wage growth", "value": 14, "unit": "percentage_points", "basis": "Difference between the published cumulative changes (29% minus 15%); the report separately projects a 14.2 percentage-point gap for 2024 in its chapter 3 discussion.", "source_ids": [ "ilo-gwr-2024-25" ] } ], "limitations": [ "The comparison is between two economy-wide averages, not between productivity and the pay of a typical or median worker; it does not account for wage inequality within countries.", "Productivity is measured as GDP per worker, not output per hour, and real wages are deflated with the CPI; the report notes that using the GDP deflator changes magnitudes but not the direction of the gap.", "Most of the cumulative gap arose between 1999 and 2006; afterwards the two indices moved roughly in parallel apart from crisis-related deviations, so the 29% versus 15% totals should not be read as steady annual divergence.", "2024 values use only first- and second-quarter data and the report describes part of the 2024 gap as projected.", "The sample is 52 high-income countries and excludes low- and middle-income economies; population weighting means large countries dominate the averages.", "The report documents the gap and discusses possible mechanisms without identifying a single cause, and it does not analyse AI adoption." ], "relevance": { "supports": "In high-income countries, average labour productivity has grown substantially faster than average real wages over the current century, so productivity gains have not translated one-for-one into pay.", "does_not_establish": [ "That AI caused the gap", "That a 32-hour week is affordable, feasible or costless", "The pay of the median or typical worker within any country", "Causal mechanisms behind decoupling", "Wage and productivity trends in low- and middle-income countries" ] }, "sources": [ { "id": "ilo-gwr-2024-25", "title": "Global Wage Report 2024–25: Is wage inequality decreasing globally?", "publisher": "International Labour Organization", "authors": [ "International Labour Organization" ], "url": "https://www.ilo.org/publications/flagship-reports/global-wage-report-2024-25-wage-inequality-decreasing-globally", "doi": "10.54394/CJQU6666", "full_text_url": "https://www.ilo.org/sites/default/files/2025-01/GWR-2024-25.pdf", "published": "2024-11-28", "source_type": "international_organization_report", "primary": true, "accessed": "2026-10-31", "checked_sections": [ "Publication details and date (28 November 2024)", "Executive summary, key finding on labour productivity versus real wages in high-income countries", "Chapter 3, section 3.4 'Wages and productivity trends in high-income countries'", "Figure 3.5 and its notes (52 countries, index base 1999, population weights, GDP per worker, 2024 Q1–Q2 data)", "Copyright page (ISBN, ISSN, DOI)" ] } ], "verification": { "verified_on": "2026-10-31", "method": "primary_source_check", "checked_source_ids": [ "ilo-gwr-2024-25" ], "replicated": false, "notes": "Read the ILO publication page and the full report PDF, including the executive-summary sentence reporting 29% productivity growth against 15% real wage growth for 1999–2024, and the chapter 3 figure notes. Did not reproduce the ILO indices from IMF and ILOSTAT data." } }, { "schema_version": "1.0", "id": "metr-2025-developer-productivity", "status": "verified", "claim_type": "empirical", "topic": "ai_productivity", "updated": "2026-10-31", "period": "February–June 2025", "primary_source_id": "becker-rush-barnes-rein-2025", "summary": { "finding": "In a randomized trial involving 16 experienced open-source developers and 246 real issues, tasks with AI allowed took 19% longer to complete than tasks with AI disallowed.", "scope": "The study used early-2025 tools in large, mature repositories and measured completion time; it does not show how all developers, other tasks or later AI tools perform." }, "population": { "description": "Experienced open-source developers contributing to large, mature repositories; 16 developers and 246 tasks.", "geographies": [ "Not reported" ], "samples": [ { "group": "Developers", "n": 16, "unit": "developers" }, { "group": "Randomized tasks", "n": 246, "unit": "tasks" } ] }, "method": { "design": "randomized_controlled_trial", "description": "Each issue was randomly assigned to AI-allowed or AI-disallowed; developers worked on their own repositories and recorded completion time, with screen recordings.", "intervention": "Access to early-2025 AI tools, primarily Cursor Pro with Claude 3.5/3.7 Sonnet.", "comparator": "The same developers working on AI-disallowed issues without generative AI assistance." }, "results": [ { "id": "completion-time-change", "measure": "Task completion time with AI allowed versus AI disallowed", "value": 19, "unit": "percent_increase", "basis": "AI-allowed tasks took 19% longer; the authors describe this as a 19% slowdown. METR's 2026 update reports a confidence interval of +2% to +39%.", "source_ids": [ "becker-rush-barnes-rein-2025", "metr-2026-uplift-update" ] }, { "id": "forecast-speedup", "measure": "Developer forecast of AI speedup before tasks", "value": 24, "unit": "percent_expected_reduction_in_completion_time", "basis": "Participating developers forecast that allowing AI would reduce completion time by 24%.", "source_ids": [ "becker-rush-barnes-rein-2025" ] }, { "id": "post-study-perceived-speedup", "measure": "Developer estimate of AI speedup after the study", "value": 20, "unit": "percent_perceived_reduction_in_completion_time", "basis": "After completing the study, developers estimated that allowing AI had reduced completion time by 20%.", "source_ids": [ "becker-rush-barnes-rein-2025" ] }, { "id": "later-study-original-developers", "measure": "Completion-time change in METR's later experiment, original developers", "value": -18, "unit": "percent_change_in_completion_time", "basis": "Negative value means 18% faster. METR's February 2026 follow-up reports a confidence interval of -38% to +9%; newly recruited developers were -4% (CI -15% to +9%). The authors caution that selection effects make these later estimates weak evidence.", "source_ids": [ "metr-2026-uplift-update" ] } ], "limitations": [ "Sixteen experienced developers at large, mature open-source repositories; not representative of all developers or workplaces.", "Task-level randomization with self-recorded completion time; average task length was about two hours.", "The study used early-2025 tools (Cursor Pro with Claude 3.5/3.7 Sonnet); results may not generalize to later models or other tasks.", "METR's February 2026 follow-up reports raw speedup estimates for later tools but cautions that selection effects make the new data unreliable; the 2025 estimate is historical.", "The study measures time on issues, not output quality, wages, hours or employment." ], "relevance": { "supports": "AI tools can fail to raise, and may reduce, measured productivity for experienced developers in some real-world settings.", "does_not_establish": [ "That AI never helps developers", "Economy-wide productivity effects", "Effects on hours, pay or employment", "That a shorter working week is affordable" ] }, "sources": [ { "id": "becker-rush-barnes-rein-2025", "title": "Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity", "publisher": "METR", "authors": [ "Joel Becker", "Nate Rush", "Beth Barnes", "David Rein" ], "url": "https://arxiv.org/abs/2507.09089", "doi": "10.48550/arXiv.2507.09089", "full_text_url": "https://arxiv.org/pdf/2507.09089", "published": "2025-07-10", "source_type": "working_paper", "primary": true, "accessed": "2026-10-31", "checked_sections": [ "Abstract", "Introduction", "Section 2.1 Developers and Repositories", "Figure 1" ] }, { "id": "metr-2026-uplift-update", "title": "We are Changing our Developer Productivity Experiment Design", "publisher": "METR", "authors": [ "Joel Becker", "Nate Rush", "Tom Cunningham", "David Rein", "Khalid Mahamud" ], "url": "https://metr.org/blog/2026-02-24-uplift-update/", "published": "2026-02-24", "source_type": "research_update", "primary": false, "accessed": "2026-10-31", "checked_sections": [ "Summary of the original and later experiments", "Raw results for original and newly recruited developers", "Selection-effect caveats" ] } ], "verification": { "verified_on": "2026-10-31", "method": "primary_source_check", "checked_source_ids": [ "becker-rush-barnes-rein-2025", "metr-2026-uplift-update" ], "replicated": false, "notes": "Read the arXiv paper's abstract, introduction, Section 2.1 and Figure 1. METR's February 24, 2026 update reports later estimates but cautions that selection effects make them weak evidence; METR also labels the 2025 result out of date." } }, { "schema_version": "1.0", "id": "nhb-2025-four-day-wellbeing", "status": "verified", "claim_type": "empirical", "topic": "working_time", "updated": "2026-10-31", "period": "Six-month trials across cohorts in 2022–2024", "primary_source_id": "fan-schor-kelly-gu-2025", "summary": { "finding": "A six-month shorter-week study found improved self-reported well-being among 2,896 employees in 141 organizations, a pattern absent in 12 control organizations.", "scope": "Nonrandomized, income-preserving trials in six countries; schedules and hours varied." }, "population": { "description": "Employees in participating organizations", "geographies": [ "Australia", "Canada", "Ireland", "New Zealand", "United Kingdom", "United States" ], "samples": [ { "group": "Trial analysis", "n": 2896, "unit": "employees" }, { "group": "Trial organizations", "n": 141, "unit": "organizations" }, { "group": "Control analysis", "n": 285, "unit": "employees" }, { "group": "Control organizations", "n": 12, "unit": "organizations" } ] }, "method": { "design": "nonrandomized_controlled_intervention", "description": "Pre/post surveys with comparison organizations.", "intervention": "Work reorganization followed by reduced hours without reduced pay.", "comparator": "Organizations interested in shorter hours that did not join the trials." }, "results": [ { "id": "wellbeing-direction", "measure": "Burnout, job satisfaction, mental and physical health", "value": "improved", "unit": "reported_direction", "basis": "Self-reported pre/post changes; no comparable pattern in controls.", "source_ids": [ "fan-schor-kelly-gu-2025" ] }, { "id": "weekly-hours-change", "measure": "Mean individual weekly hours", "value": -4.72, "unit": "hours_per_week_change", "basis": "Trial group: 38.98 to 34.26 hours; not a uniform 32-hour week.", "source_ids": [ "fan-schor-kelly-gu-2025" ] } ], "limitations": [ "Organizations self-selected; assignment was not randomized.", "Outcomes were self-reported; participating firms were not representative.", "Control observations largely came from a later period." ], "relevance": { "supports": "Reduced paid working time was associated with improved well-being in participating organizations.", "does_not_establish": [ "AI financed the reduction", "Universal feasibility", "A uniform 32-hour schedule" ] }, "sources": [ { "id": "fan-schor-kelly-gu-2025", "title": "Work time reduction via a 4-day workweek finds improvements in workers’ well-being", "publisher": "Nature Human Behaviour", "authors": [ "Wen Fan", "Juliet B. Schor", "Orla Kelly", "Guolin Gu" ], "url": "https://www.nature.com/articles/s41562-025-02259-6", "doi": "10.1038/s41562-025-02259-6", "full_text_url": "https://par.nsf.gov/servlets/purl/10636509", "abstract_url": "https://pubmed.ncbi.nlm.nih.gov/40691306/", "published": "2025-07-21", "source_type": "peer_reviewed_article", "primary": true, "accessed": "2026-10-31", "checked_sections": [ "Abstract", "Tables 1–2", "Methods", "Limitations and future directions" ] } ], "verification": { "verified_on": "2026-10-31", "method": "primary_source_check", "checked_source_ids": [ "fan-schor-kelly-gu-2025" ], "replicated": false, "notes": "Checked the article's NSF-hosted full text and PubMed metadata; publisher access redirected to an unavailable cookie endpoint." } }, { "schema_version": "1.0", "id": "owid-2023-working-hours", "status": "verified", "claim_type": "empirical", "topic": "working_time", "updated": "2026-10-31", "period": "1870–2023", "primary_source_id": "owid-annual-working-hours", "summary": { "finding": "Published estimates put US annual working hours per worker at about 3,100 in 1870 and 1,790 in 2023, with large declines also shown for Germany and the UK.", "scope": "Historical figures cover full-time production workers, while post-1950 averages include the whole economy and part-time work; these annual estimates are not a uniform measure of weekly hours." }, "population": { "description": "Workers in the United States, Germany and the United Kingdom as represented by national estimates of average annual hours worked per worker.", "geographies": [ "United States", "Germany", "United Kingdom" ], "samples": [] }, "method": { "design": "observational_series", "description": "Our World in Data publishes country-year estimates of average annual hours worked per worker. The series splices Huberman and Minns (2005), covering full-time production workers in non-agricultural activities for 1870–1938, with Penn World Table 11.0 (2025) hours worked per worker for 1950–2023.", "intervention": "Not applicable; no intervention was assigned.", "comparator": "Earlier years of the same country series and the same year across the three countries." }, "results": [ { "id": "us-hours-1870", "measure": "Average annual hours worked per worker", "value": 3096, "unit": "hours_per_worker_per_year", "basis": "United States, 1870; Huberman and Minns (2005) estimate for full-time production workers in non-agricultural activities.", "source_ids": [ "owid-annual-working-hours" ] }, { "id": "us-hours-2023", "measure": "Average annual hours worked per worker", "value": 1788.88, "unit": "hours_per_worker_per_year", "basis": "United States, 2023; Penn World Table 11.0 total-economy estimate, the latest year in the series.", "source_ids": [ "owid-annual-working-hours" ] }, { "id": "germany-hours-1870", "measure": "Average annual hours worked per worker", "value": 3284, "unit": "hours_per_worker_per_year", "basis": "Germany, 1870; Huberman and Minns (2005) estimate for full-time production workers in non-agricultural activities.", "source_ids": [ "owid-annual-working-hours" ] }, { "id": "germany-hours-2023", "measure": "Average annual hours worked per worker", "value": 1335.27, "unit": "hours_per_worker_per_year", "basis": "Germany, 2023; Penn World Table 11.0 total-economy estimate, the latest year in the series.", "source_ids": [ "owid-annual-working-hours" ] }, { "id": "uk-hours-1870", "measure": "Average annual hours worked per worker", "value": 2755, "unit": "hours_per_worker_per_year", "basis": "United Kingdom, 1870; Huberman and Minns (2005) estimate for full-time production workers in non-agricultural activities.", "source_ids": [ "owid-annual-working-hours" ] }, { "id": "uk-hours-2023", "measure": "Average annual hours worked per worker", "value": 1522.8, "unit": "hours_per_worker_per_year", "basis": "United Kingdom, 2023; Penn World Table 11.0 total-economy estimate, the latest year in the series.", "source_ids": [ "owid-annual-working-hours" ] } ], "limitations": [ "The series splices two sources with different populations and definitions: before 1950 it covers only full-time production workers in non-agricultural activities, while from 1950 it covers all employees and the self-employed economy-wide. The break is visible in the data (US 1,756 hours in 1938 versus 2,021.98 in 1950), so year-on-year changes across the splice are not comparable.", "These are estimates assembled from historical and national-accounts sources with changing country coverage and measurement methods, not one harmonised survey.", "Annual hours per worker is not weekly hours; it does not show the distribution of hours within a country, second jobs, unpaid work, or the share of workers on any particular weekly schedule.", "Post-1950 averages include part-time workers and are not restricted to full-time schedules.", "Values can be revised when Our World in Data updates the underlying Penn World Table or historical series; the recorded snapshot is the version updated 2025-08-05." ], "relevance": { "supports": "Average annual hours worked per worker in the United States, Germany and the United Kingdom were far lower in 2023 than in 1870, and long-run working time has fallen substantially in early-industrialising economies.", "does_not_establish": [ "That a 32-hour week is feasible, affordable or costless", "That AI or any single technology caused the long-run decline in hours", "Current weekly hours, overtime or the distribution of hours across workers", "That shorter hours raise productivity", "Causal effects of any working-time policy" ] }, "sources": [ { "id": "owid-annual-working-hours", "title": "Annual working hours per worker", "publisher": "Our World in Data", "authors": [ "Charlie Giattino", "Esteban Ortiz-Ospina", "Max Roser" ], "url": "https://ourworldindata.org/grapher/annual-working-hours-per-worker", "updated": "2025-08-05", "source_type": "research_organization_dataset", "primary": true, "accessed": "2026-10-31", "checked_sections": [ "Chart title, subtitle and source note", "Grapher column metadata for 'Working hours per worker' (unit, timespan 1870-2023, lastUpdated 2025-08-05, Variable ID 1103669, processing note)", "Downloaded CSV: values for United States, Germany and United Kingdom, 1870-2023", "Working Hours topic page byline, citation and description" ] } ], "verification": { "verified_on": "2026-10-31", "method": "primary_source_check", "checked_source_ids": [ "owid-annual-working-hours" ], "replicated": false, "notes": "Read the Our World in Data chart page, its Grapher metadata JSON (last updated 2025-08-05; next update 2026-12-01) and the full CSV download, and recorded the published values without recomputation. Underlying Huberman and Minns (2005) and Penn World Table 11.0 (2025) files were not separately opened." } }, { "schema_version": "1.0", "id": "qje-2025-generative-ai-at-work", "status": "verified", "claim_type": "empirical", "topic": "ai_productivity", "updated": "2026-10-31", "period": "AI rollout mainly in fall 2020 and winter 2021", "primary_source_id": "brynjolfsson-li-raymond-2025", "summary": { "finding": "AI assistance increased issues resolved per hour by 15% on average in a study of 5,172 customer-support agents at one firm and its contractors.", "scope": "Mostly Philippines-based agents serving US customers; effects varied by experience." }, "population": { "description": "Business-software technical support agents", "geographies": [ "Philippines", "United States", "Other countries" ], "samples": [ { "group": "Full study sample", "n": 5172, "unit": "agents" } ] }, "method": { "design": "quasi_experimental", "description": "Staggered AI rollout; difference-in-differences with agent, calendar and tenure controls.", "intervention": "AI suggests chat responses; agents retain control.", "comparator": "Agents before access and agents without access." }, "results": [ { "id": "resolved-issues-per-hour", "measure": "Issues resolved per hour", "value": 15, "unit": "percent_relative_increase", "basis": "Rounded headline estimate; preferred regression reports 15.2%.", "source_ids": [ "brynjolfsson-li-raymond-2025" ] } ], "limitations": [ "One business and task setting; the main rollout analysis was not randomized.", "Resolution metrics cover a subset of the full sample.", "Experienced workers gained less; some quality measures declined among the most skilled." ], "relevance": { "supports": "AI can raise output per hour in a specific workplace.", "does_not_establish": [ "Economy-wide gains", "Shorter paid working weeks", "A universal productivity multiplier" ] }, "sources": [ { "id": "brynjolfsson-li-raymond-2025", "title": "Generative AI at Work", "publisher": "The Quarterly Journal of Economics", "authors": [ "Erik Brynjolfsson", "Danielle Li", "Lindsey Raymond" ], "url": "https://academic.oup.com/qje/article/140/2/889/7990658", "doi": "10.1093/qje/qjae044", "published": "2025-02-04", "source_type": "peer_reviewed_article", "primary": true, "accessed": "2026-10-31", "checked_sections": [ "Abstract", "III.B", "IV.A–C", "V.A–B", "Tables I–II" ] } ], "verification": { "verified_on": "2026-10-31", "method": "primary_source_check", "checked_source_ids": [ "brynjolfsson-li-raymond-2025" ], "replicated": false, "notes": "Checked the final journal article, not an earlier working-paper estimate." } }, { "schema_version": "1.0", "id": "scotland-2025-public-sector-32-hour", "status": "verified", "claim_type": "empirical", "topic": "working_time", "updated": "2026-10-31", "period": "SOSE pilot from 2 October 2023 and AiB pilot from 14 April 2024, each for one year; evaluation published 27 August 2025", "primary_source_id": "autonomy-scotland-2025", "summary": { "finding": "Two Scottish public bodies with 259 staff trialed a 32-hour full-time week without pay cuts for one year, broadly maintained internal service metrics, and reported improved staff wellbeing; both extended the pilot.", "scope": "This was a before-and-after evaluation without a control group; wellbeing was self-reported, and the results do not show that every workplace could achieve the same outcome." }, "population": { "description": "Staff at two Scottish public-sector organizations that volunteered for a year-long 32-hour-week pilot.", "geographies": [ "Scotland", "United Kingdom" ], "samples": [ { "group": "Combined pilot workforce (AiB and SOSE)", "n": 259, "unit": "employees" }, { "group": "Accountant in Bankruptcy staff", "n": 119, "unit": "employees" }, { "group": "South of Scotland Enterprise staff", "n": 140, "unit": "employees" }, { "group": "Pilot organizations", "n": 2, "unit": "organizations" } ] }, "method": { "design": "nonrandomized_before_after_mixed_methods", "description": "Independent evaluation commissioned by the Scottish Government, using organizational key performance indicators, repeated staff surveys, and in-depth interviews; each organization compared pilot-period process data with the prior year and internal targets.", "intervention": "A 32-hour full-time week scheduled over four days with no loss of pay or benefits, implemented across each organization; AiB moved from 37 hours and SOSE from 35 hours.", "comparator": "The same organizations' prior-year performance and internal target times; no randomized control group." }, "results": [ { "id": "employees-covered", "measure": "Employees covered by the 32-hour week pilot", "value": 259, "unit": "employees", "basis": "Combined workforce of Accountant in Bankruptcy (119 staff) and South of Scotland Enterprise (140 staff) in 2024-25.", "source_ids": [ "autonomy-scotland-2025" ] }, { "id": "opt-in", "measure": "Staff who opted into the 32-hour pilot", "value": 258, "unit": "employees", "basis": "258 of the 259 staff across the two organizations opted in; one SOSE staff member opted out because they were due to retire.", "source_ids": [ "autonomy-scotland-2025" ] }, { "id": "weekly-hours", "measure": "Standard full-time week under the pilot", "value": 32, "unit": "hours_per_week", "basis": "Reduced from 37 hours at AiB and 35 hours at SOSE, with no loss of pay or benefits; 32 hours were scheduled over four days.", "source_ids": [ "autonomy-scotland-2025" ] }, { "id": "aib-processing-time", "measure": "Average personal bankruptcy application processing time", "value": 7.1, "unit": "days", "basis": "First three quarters of 2024-25 during the pilot versus 7.6 days in the same period a year prior; internal target was 9 days. Caseload was 1,533 in the prior-year comparison and 1,530 during the pilot.", "source_ids": [ "autonomy-scotland-2025" ] }, { "id": "sose-sla", "measure": "Service-level agreement performance on client response times", "value": 92.04, "unit": "percent", "basis": "SOSE SLA fell from 94.42% in the prior year to 92.04% during the pilot, a decrease of about 2.4%, while enquiries rose 11.4% and the number answered within target rose from 1,235 to 1,341; the report treats client response times as not significantly disrupted.", "source_ids": [ "autonomy-scotland-2025" ] }, { "id": "aib-mental-health", "measure": "Self-rated mental health score", "value": 18.4, "unit": "percent_change", "basis": "Mean score rose from 2.8 to 3.3 on a 1-5 scale from baseline to endpoint among AiB staff.", "source_ids": [ "autonomy-scotland-2025" ] }, { "id": "aib-work-stress", "measure": "Frequency of reported work stress", "value": -18.4, "unit": "percent_change", "basis": "Mean score fell from 2.8 to 2.3 on a 1-5 scale from baseline to endpoint among AiB staff.", "source_ids": [ "autonomy-scotland-2025" ] }, { "id": "aib-time-satisfaction", "measure": "Satisfaction with time for things one likes doing", "value": 46.8, "unit": "percent_change", "basis": "Mean score rose from 5.1 to 7.5 on a 0-10 scale from baseline to endpoint among AiB staff.", "source_ids": [ "autonomy-scotland-2025" ] }, { "id": "sose-work-life-balance", "measure": "Staff very satisfied with work-life balance", "value": 84, "unit": "percent", "basis": "Rose from 4% pre-pilot to 84% nine months into the SOSE pilot; 135 staff (96% of the SOSE workforce) responded at baseline and 129 (92%) at follow-up.", "source_ids": [ "autonomy-scotland-2025" ] }, { "id": "sose-psychological-sick-days", "measure": "Sick days taken for psychological reasons", "value": -25.7, "unit": "percent_change", "basis": "357 days in the year prior to 265 during the pilot at SOSE; overall sick absence as a share of available working days rose 0.6 percentage points, and sickness instances fell from 122 to 119.", "source_ids": [ "autonomy-scotland-2025" ] }, { "id": "continuation", "measure": "Pilot continuation", "value": "both organizations extended", "unit": "reported_direction", "basis": "SOSE was permitted a six-month extension and AiB a two-month extension beyond the research period.", "source_ids": [ "autonomy-scotland-2025" ] } ], "limitations": [ "Only two public-sector organizations and 259 staff; findings are not representative of the private sector or the wider workforce.", "The organizations volunteered and were not randomly assigned; there is no control group.", "Wellbeing outcomes are self-reported, and some SOSE measures lacked a live baseline because its pilot began before the evaluation commission.", "Service performance is measured by internal KPIs and processing times, not output per hour or full economic cost.", "AiB's absence data were affected by an ongoing Oracle Cloud management-system migration, and the pilots coincided with other organizational changes; the evaluation period was one year.", "A 32-hour week was delivered through a four-day schedule with staggered days off, not a uniform national 32-hour policy." ], "relevance": { "supports": "A 32-hour, four-day week with no pay cut can be implemented across whole public-sector organizations while internal processing times and service levels remain broadly stable, alongside improved self-reported wellbeing.", "does_not_establish": [ "AI financed the reduction", "Universal feasibility", "A uniform 32-hour schedule", "That the shorter week caused the wellbeing or performance changes rather than concurrent factors", "Long-term service, cost, or employment outcomes", "That the results generalize to private-sector or customer-facing organizations" ] }, "sources": [ { "id": "autonomy-scotland-2025", "title": "Introducing a Shorter Working Week in Scotland's Public Sector", "publisher": "The Autonomy Institute", "authors": [ "Will Stronge", "David Frayne", "Tatiana Pignon", "Kyle Lewis", "Niamh Bridson-Hubbard", "Rachel Limage", "Liam Mullally" ], "url": "https://autonomy.work/wp-content/uploads/2025/08/Scotland_SWW_PublicSector.pdf", "published": "2025-08-27", "source_type": "research_report", "primary": true, "accessed": "2026-10-31", "checked_sections": [ "Executive summary", "The 32-hour week pilot", "Part 1: organisational impacts", "Part 2: staff impacts", "Part 3: qualitative findings", "Recommendations" ] } ], "verification": { "verified_on": "2026-10-31", "method": "primary_source_check", "checked_source_ids": [ "autonomy-scotland-2025" ], "replicated": false, "notes": "Read the 81-page Autonomy Institute report PDF downloaded from the publisher and extracted its executive summary, organizational-impact, staff-impact, and recommendations sections. Publication date and headline figures were cross-checked against the Autonomy portfolio page dated 27 August 2025. No independent replication." } }, { "schema_version": "1.0", "id": "sweden-norway-2026-four-day-week", "status": "verified", "claim_type": "empirical", "topic": "working_time", "updated": "2026-10-31", "period": "Six-month pilot from January to June 2024; results published 2 February 2026", "primary_source_id": "karlstad-sweden-norway-2026", "summary": { "finding": "A six-month pilot in 11 Swedish and Norwegian organizations reduced working time with full pay and was associated with less stress, better sleep and higher self-reported productivity; 10 organizations continued.", "scope": "Schedules varied, including shorter days, and the before-and-after study had no control group, so it does not establish causal effects or a uniform 32-hour week." }, "population": { "description": "Employees and organizations in a six-month Nordic pilot of reduced working hours under the 100:80:100 model.", "geographies": [ "Sweden", "Norway" ], "samples": [ { "group": "Participating organizations", "n": 11, "unit": "organizations" }, { "group": "Pre-pilot employee survey respondents", "n": 269, "unit": "employees" }, { "group": "Post-pilot employee survey respondents", "n": 212, "unit": "employees" }, { "group": "In-depth interviews", "n": 77, "unit": "interviews" } ] }, "method": { "design": "nonrandomized_within_group_pre_post", "description": "Six-month pilot with pre- and post-employee surveys, organizational surveys, 77 interviews, 143 diary entries, and operational data on results and sick leave; no control group.", "intervention": "Reduced working hours to about 80% of prior time with 100% pay under the 100:80:100 model; organizations chose four-day, rotating-day-off, or six-hour-day arrangements.", "comparator": "Within-group change from pre- to post-pilot; no control group." }, "results": [ { "id": "organizations", "measure": "Organizations participating in the pilot", "value": 11, "unit": "organizations", "basis": "Nine Swedish and two Norwegian organizations; one two-person consulting firm ended early and one acquired firm was excluded from the report's analysis.", "source_ids": [ "karlstad-sweden-norway-2026" ] }, { "id": "employee-survey-pre", "measure": "Employees responding to the pre-pilot survey", "value": 269, "unit": "employees", "basis": "Pre-measurement survey respondents; 212 employees responded at post-measurement.", "source_ids": [ "karlstad-sweden-norway-2026" ] }, { "id": "stress-change", "measure": "Self-reported stress", "value": -19, "unit": "percent_change", "basis": "Mean stress fell from 3.2 to 2.6 on a five-point scale.", "source_ids": [ "karlstad-sweden-norway-2026" ] }, { "id": "perceived-productivity", "measure": "Self-reported productivity", "value": 13, "unit": "percent_change", "basis": "Mean perceived productivity rose from 7.1 to 8.0 on a 10-point scale; work ability rose 10%, from 7.1 to 7.8.", "source_ids": [ "karlstad-sweden-norway-2026" ] }, { "id": "sleep-duration", "measure": "Self-reported nightly sleep", "value": 24, "unit": "minutes_per_night", "basis": "Mean sleep duration rose from 6.6 to 7.0 hours per night.", "source_ids": [ "karlstad-sweden-norway-2026" ] }, { "id": "continuation", "measure": "Organizations continuing after the pilot", "value": 10, "unit": "organizations", "basis": "Ten of eleven businesses chose to continue after the six-month pilot; some made shorter weeks permanent and others extended the pilot.", "source_ids": [ "karlstad-sweden-norway-2026" ] }, { "id": "financial-results", "measure": "Financial results compared with the same period a year earlier", "value": "none worse", "unit": "reported_direction", "basis": "Of the ten businesses reporting operational results, none had a worse financial outcome; some improved and others were unchanged.", "source_ids": [ "karlstad-sweden-norway-2026" ] }, { "id": "sick-leave-reductions", "measure": "Organizations reporting reduced sick leave", "value": 8, "unit": "organizations", "basis": "Eight businesses reported reduced sick leave, in a range of 3% to 100%; ten businesses reported operational results.", "source_ids": [ "karlstad-sweden-norway-2026" ] } ], "limitations": [ "Within-group design without a control group; changes cannot be attributed solely to shorter hours.", "Small sample: 11 organizations and 269 pre- and 212 post-survey employees; one two-person firm ended early and one acquired firm was excluded.", "Outcomes are self-reported, and the report says the statistically significant changes are generally small.", "The pilot lasted six months, so long-term sustainability is not established.", "Operational and financial data covered only ten organizations and were not independently audited.", "Schedules varied across organizations; this was not a uniform 32-hour week." ], "relevance": { "supports": "Reduced working hours combined with work redesign was associated with lower stress, better sleep, and higher self-reported productivity in participating Nordic organizations, and most continued.", "does_not_establish": [ "AI financed the reduction", "Universal feasibility", "A uniform 32-hour schedule", "Causal attribution because the design lacks a control group", "That financial results improved in every organization", "Long-term effects beyond the six-month pilot" ] }, "sources": [ { "id": "karlstad-sweden-norway-2026", "title": "4 Day Week Sweden & Norway: A Study on Reduced Working Hours, Smarter Ways of Working, and Their Impact on Working Life", "publisher": "Karlstad University and The Rework", "authors": [ "Lena Lid Falkman", "Siri Jakobsson Støre", "Anna-Carin Alderin", "Sarah Uldal", "Daniela Tell" ], "url": "https://kau.diva-portal.org/smash/get/diva2:2060944/FULLTEXT01.pdf", "published": "2026-02-02", "source_type": "research_report", "primary": true, "accessed": "2026-10-31", "checked_sections": [ "Summary", "The pilot in practice", "Research and academic insights", "Results" ] }, { "id": "rework-sweden-norway-2026", "title": "Ny svensk-norsk forskningsstudie: Kortare arbetsveckor stärker både välmående och verksamhetsresultat", "publisher": "The Rework", "authors": [ "The Rework" ], "url": "https://www.therework.se/artiklar/nyforskningsstudie", "published": "2026-02-02", "source_type": "publisher_announcement", "primary": false, "accessed": "2026-10-31", "checked_sections": [ "Publication date", "Study sample", "Headline results" ] } ], "verification": { "verified_on": "2026-10-31", "method": "primary_source_check", "checked_source_ids": [ "karlstad-sweden-norway-2026", "rework-sweden-norway-2026" ], "replicated": false, "notes": "Read the 103-page Karlstad University report PDF from DiVA and extracted the summary, pilot design, research note, and results. Publication date was cross-checked on The Rework's 2 February 2026 announcement. The report cover says February 2026, its imprint says April 2026, and PDF metadata says May 2026; the 2 February 2026 announcement is used. No independent replication." } } ] }