Evidence (7953 claims)
Adoption
5539 claims
Productivity
4793 claims
Governance
4333 claims
Human-AI Collaboration
3326 claims
Labor Markets
2657 claims
Innovation
2510 claims
Org Design
2469 claims
Skills & Training
2017 claims
Inequality
1378 claims
Evidence Matrix
Claim counts by outcome category and direction of finding.
| Outcome | Positive | Negative | Mixed | Null | Total |
|---|---|---|---|---|---|
| Other | 402 | 112 | 67 | 480 | 1076 |
| Governance & Regulation | 402 | 192 | 122 | 62 | 790 |
| Research Productivity | 249 | 98 | 34 | 311 | 697 |
| Organizational Efficiency | 395 | 95 | 70 | 40 | 603 |
| Technology Adoption Rate | 321 | 126 | 73 | 39 | 564 |
| Firm Productivity | 306 | 39 | 70 | 12 | 432 |
| Output Quality | 256 | 66 | 25 | 28 | 375 |
| AI Safety & Ethics | 116 | 177 | 44 | 24 | 363 |
| Market Structure | 107 | 128 | 85 | 14 | 339 |
| Decision Quality | 177 | 76 | 38 | 20 | 315 |
| Fiscal & Macroeconomic | 89 | 58 | 33 | 22 | 209 |
| Employment Level | 77 | 34 | 80 | 9 | 202 |
| Skill Acquisition | 92 | 33 | 40 | 9 | 174 |
| Innovation Output | 120 | 12 | 23 | 12 | 168 |
| Firm Revenue | 98 | 34 | 22 | — | 154 |
| Consumer Welfare | 73 | 31 | 37 | 7 | 148 |
| Task Allocation | 84 | 16 | 33 | 7 | 140 |
| Inequality Measures | 25 | 77 | 32 | 5 | 139 |
| Regulatory Compliance | 54 | 63 | 13 | 3 | 133 |
| Error Rate | 44 | 51 | 6 | — | 101 |
| Task Completion Time | 88 | 5 | 4 | 3 | 100 |
| Training Effectiveness | 58 | 12 | 12 | 16 | 99 |
| Worker Satisfaction | 47 | 32 | 11 | 7 | 97 |
| Wages & Compensation | 53 | 15 | 20 | 5 | 93 |
| Team Performance | 47 | 12 | 15 | 7 | 82 |
| Automation Exposure | 24 | 22 | 9 | 6 | 62 |
| Job Displacement | 6 | 38 | 13 | — | 57 |
| Hiring & Recruitment | 41 | 4 | 6 | 3 | 54 |
| Developer Productivity | 34 | 4 | 3 | 1 | 42 |
| Social Protection | 22 | 10 | 6 | 2 | 40 |
| Creative Output | 16 | 7 | 5 | 1 | 29 |
| Labor Share of Income | 12 | 5 | 9 | — | 26 |
| Skill Obsolescence | 3 | 20 | 2 | — | 25 |
| Worker Turnover | 10 | 12 | — | 3 | 25 |
The machine-learning based analytical approach used in the study captures complex, nonlinear relationships among emotional, psychological and economic variables.
Methodological claim: authors used machine learning (including ensembles) to model nonlinear and complex relationships. The excerpt does not provide algorithmic details, tuning, validation strategy, or sample size.
Work environment and digital/AI intensity were incorporated as contextual moderators in the analysis to reflect contemporary labor market conditions.
Methodological description in the excerpt states these variables were included as moderators; no details on measurement, operationalization, or sample size are provided.
Most evidence came from retrospective studies or meta-analyses, with limited prospective or randomized controlled trials.
Summary of study designs across the 40 included studies as reported in the review.
The impact of AI on patient outcomes (e.g., mortality, rebleeding) was rarely addressed.
Statement in results indicating few included studies reported patient-centered outcomes such as mortality or rebleeding.
This systematic review adhered to PRISMA 2020 guidelines.
Methods statement in the paper specifying adherence to PRISMA 2020; the review included 40 studies.
Coordination is treated as a structural property of the coupled dynamics (agents + incentives + persistent environment) rather than as the solution to a centralized global optimization objective or purely agent-centric learning problem.
Conceptual framing supported by the formal dynamical model and theorems showing properties of the closed-loop dynamics that do not rely on an underlying global objective.
The persistent environment component of the model stores accumulated coordination signals, and a distributed incentive field transmits those signals locally to adaptive agents, which update their states in response.
Model construction and definitions in the paper describing (i) an environmental state variable with persistent dynamics that accumulates signals, (ii) a spatially/distributed incentive field mapping environmental memory to local agent inputs, and (iii) adaptive update rules for agents.
The paper formalizes agents, incentives, and the environment as a recursively closed feedback architecture (i.e., a coupled dynamical system in which agents adapt to incentive signals that themselves depend on a persistent environmental memory produced by agent actions).
Mathematical model and definitions presented in the paper (formal system specification of agent states, incentive field, and persistent environment; no empirical data).
The review focuses on AI applications within small‑scale business environments, with a special focus on women‑owned micro firms in Jaipur, India.
Scope and aim articulated in the paper; geographic and demographic focus explicitly stated by the authors.
The systematic review follows PRISMA 2020 guidelines.
Methodological statement in the paper indicating adherence to PRISMA 2020 for the review process.
After screening and eligibility filtering, 55 open‑access journal articles were included for in‑depth analysis.
PRISMA‑guided screening and eligibility process reported in the review; final included sample explicitly stated as 55 open‑access journal articles.
A Scopus search identified 265 records using keywords related to women’s entrepreneurship and AI.
Systematic literature search reported in the paper following PRISMA 2020; search executed in Scopus with specified keywords; initial yield stated as 265 records.
This research examined three countries (China, the United States, and Germany) using panel vector autoregressive (panel VAR) and difference-in-differences (DID) methods to assess how technology and public policy interventions affect emissions reductions.
Study design reported in the paper: sample of three countries (China, US, Germany) and application of panel VAR and DID methods; specific time period and sample size not provided in the summary.
Social assistance (SA) is defined here as noncontributory social transfers (including cash, vouchers, or in-kind transfers to families or individuals, including the elderly), public works programs, fee waivers, and subsidies.
Explicit definitional statement in the introduction (authors' operational definition for the chapter).
This chapter focuses on low- and middle-income countries (LMICs) and uses a 'review of reviews' approach to summarize the policy discourse and evidence on social protection and gender in adulthood, concentrating on social assistance, social care, and social insurance.
Methodological and scope statement explicitly given in the introduction (author-declared approach and focus).
This study draws on a critical AI media literacy framework to analyze user-generated discussions in the two largest higher education subreddits on Reddit.com.
Author-reported study design: application of a critical AI media literacy theoretical framework to a qualitative dataset consisting of user-generated discussions from the two largest higher-education subreddits. (Sample size/number of posts/threads not specified in the provided excerpt.)
The study used a mixed-methods design incorporating surveys from 150 LEP immigrants, interviews with 50 employers, and interviews with 20 translation service providers in various linguistically diverse U.S. cities, with quantitative analysis performed in SPSS Version 28 and qualitative thematic coding in NVivo 14.
Reported study design and sample: survey n=150 LEP immigrants; employer interviews n=50; translation provider interviews n=20; analytic software specified as SPSS v28 (quantitative) and NVivo 14 (qualitative).
Viable transition pathways are operationally defined in this study as sharing at least 3 skills and achieving at least 50% skill transfer.
Methodological definition stated in the paper used to determine whether a job-to-job transition is considered viable.
We identified 4,534 feasible transitions between jobs in the dataset.
Count of feasible job-to-job transition pairs found in the knowledge graph analysis (4,534 transitions reported).
We constructed and validated a knowledge graph of 9,978 Egyptian job postings, 19,766 skill activities, and 84,346 job-skill relationships with a 0.74% error rate.
Empirical construction and validation of a knowledge graph using a dataset of 9,978 job postings, 19,766 distinct skill/activity nodes, and 84,346 job–skill edges; reported overall error rate 0.74% (validation method not detailed in the excerpt).
In a field experiment on the DiagnosUs medical crowdsourcing platform, the authors held the true prevalence in the unlabeled stream fixed at 20% (blasts) while varying the prevalence of positives in the gold-standard feedback stream (20% vs. 50%) and the response interface (binary labels vs. elicited probabilities).
Field experiment conducted on the DiagnosUs platform with experimental manipulations: (i) true prevalence in unlabeled stream fixed at 20% blasts, (ii) feedback-stream prevalence manipulated to 20% vs 50%, (iii) response interface manipulated between binary labels and elicited probabilities. (Sample size and number of workers not specified in the provided excerpt.)
The study examines 268 Chinese cities from 2010 to 2023 and integrates theoretical analysis with empirical testing to study AI innovation's employment effects.
Study description specifying sample size (268 cities), period (2010–2023), and combined theoretical and empirical approach.
The framework was evaluated on 2,847 queries across 15 task categories.
Paper reports an evaluation dataset consisting of 2,847 queries spanning 15 task categories; used as the sample for reported empirical results.
Non-text processing paths use SLM-assisted modality decomposition.
Paper reports that non-text queries are decomposed using SLM-assisted modality decomposition; described as the non-text routing approach in the framework.
For text-only queries, the framework uses learned routing via RouteLLM.
Paper states text-only routing is handled by a learned model named RouteLLM; presented as part of the system architecture.
A central Supervisor dynamically decomposes user queries, delegates subtasks to modality-appropriate tools (e.g., object detection, OCR, speech transcription), and synthesizes results through adaptive routing strategies rather than predetermined decision trees.
Methodological description in the paper of a Supervisor component that performs dynamic decomposition, delegation to modality-appropriate tools (examples given), and adaptive routing; supported by the framework's implementation details.
We present an agentic AI framework for autonomous multimodal query processing that coordinates specialized tools across text, image, audio, video, and document modalities.
Paper describes the framework design and components (Supervisor, modality-specific tools) and states support for text, image, audio, video, and document modalities; no external benchmark cited for this capability beyond the paper's own implementation.
The study employs an input–output (I–O) modeling framework using IMPLAN 2022 data to estimate direct, indirect, and induced impacts of investments in greenhouse and robotics sectors for Northwest Indiana as part of Project TRAVERSE.
Explicit methodological statement in the paper: use of IMPLAN 2022 I–O model; geographic scope NWI; linkage to EDA Project TRAVERSE.
We extract the Big 5 personality traits from facial images of 96,000 MBA graduates using advances in AI and LinkedIn microdata.
Methodological claim reported in the paper: AI-based model applied to facial images linked to LinkedIn microdata for a sample of 96,000 MBA graduates; extraction yields 'Photo Big 5' trait scores.
The essay reviews seven books from the past dozen years by social scientists examining the economic impact of artificial intelligence (AI).
Qualitative book-review performed by the author; sample size explicitly stated as seven books published within the last ~12 years; method = synthesis/assessment of those seven books.
This systematic review follows PRISMA guidelines to examine the evolution, advancements, and state-of-the-art AI applications for GS-BESS optimization.
Methodological statement in the paper indicating the use of PRISMA guidelines for the review process. The excerpt does not include the PRISMA flow diagram or the exact article selection numbers.
The study is limited by the scope of available industry data and the generalisability of case study findings.
Explicit limitation reported in the paper summary stating constraints related to industry data availability and generalisability of case studies.
The research adopts a mixed-method approach, combining theoretical analysis with empirical insights, and uses data gathered from the 'AI-driven transformation' Scopus database.
Explicit methodological statement in the paper summary: mixed-method design and Scopus database as the data source. (No further methodological details or sample counts provided in the summary.)
The conceptual model for the study is grounded in the Resource-Based View (RBV) and the Technology-Organization-Environment (TOE) framework.
Theory section of the paper: model development explicitly references RBV and TOE as theoretical foundations for selecting determinants and mediators.
The data were analysed using partial least squares structural equation modeling (PLS-SEM).
Methods section: PLS-SEM specified as the primary analytical technique for hypothesis testing and mediation analysis.
Data were collected via a cross-sectional survey of 312 senior managers across diverse UK industries.
Study methods: described sample = 312 senior managers from multiple UK industries; cross-sectional survey instrument and sampling reported in methods section.
The experimental sample underlying the statistical tests comprised 20 observations (implied by ANOVA degrees of freedom: df between = 1, df within = 18).
Interpretation of the reported one-way ANOVA degrees of freedom (F(1,18) for multiple outcomes) indicating total N = 20 observations.
Field experiments at the Al‐Ra'id Research Station in Baghdad during the 2025 season compared conventional diesel‐based irrigation with AI‐assisted irrigation using soil moisture sensors, IoT controllers, and predictive weather algorithms.
Reported field experiment design in the paper (Al‐Ra'id Research Station, Baghdad, 2025 season) specifying two treatments: conventional diesel irrigation vs AI-assisted irrigation using soil moisture sensors, IoT controllers, and predictive weather algorithms.
Definitions and scopes of Material Passports vary among authors.
Content analysis of the 46 included studies showing differing definitions and scope treatments for MPs reported by the authors.
Among the included studies, 65% focused primarily on Material Passports (MPs), while 35% addressed MPs within the broader context of a circular economy (CE).
Quantitative categorization of the 46 included studies reported in the paper (percentages attributed to focus areas).
A total of 54 peer-reviewed articles and book chapters were screened from the Scopus database, of which 46 were included for in-depth analysis in April 2025.
Reported screening and inclusion counts from the Scopus search (54 screened, 46 included); date of in-depth analysis given as April 2025.
This article presents a Systematic Literature Review (SLR) following the PRISMA methodology.
Stated methodology in the paper: SLR using PRISMA; literature search performed in Scopus; review process and inclusion/exclusion described (screening and inclusion counts reported).
Future research could strengthen causal identification by exploiting exogenous policy shocks rather than relying solely on matching methods like PSM.
Authors' methodological suggestion for future work, based on limitations of current causal inference strategy (PSM and observational panel regression).
Propensity Score Matching (PSM) and other robustness checks were used to mitigate selection bias and support the causal interpretation of AI's effects.
Paper reports use of Propensity Score Matching in robustness analyses on the panel of A-share-listed design firms (2014–2023).
The paper operationalizes firm-level AI exposure by constructing an AI lexicon via natural language processing and applying text analysis to annual reports and patents to generate enterprise-level AI indicators.
Described methodology: NLP to generate an AI lexicon and text-analysis of annual reports and patents to build AI measures for each listed design enterprise in the 2014–2023 panel.
The study tracked participants in a three-wave panel totaling over 1,500 workers.
Abstract reporting a three-wave panel design and a sample size of over 1,500 workers.
Task content and valence were randomized in the experiment.
Methodological statement in the abstract that task assignments, including their content and valence, were randomized across participants.
The paper presents relevant tradeoffs and design choices across human-LLM archetypes, including decision control, social hierarchies, cognitive forcing strategies, and information requirements.
Qualitative analysis and discussion in the paper synthesizing insights from the literature review and empirical evaluation. Method: thematic synthesis and design analysis. Sample size: based on the review of 113 papers and the clinical-case evaluation (details in full text).
We describe 17 human-LLM archetypes derived from a scoping literature review and thematic analysis of 113 LLM-supported decision-making papers.
Scoping literature review and thematic analysis method; corpus size = 113 LLM-supported decision-making papers (as reported in the paper).
The paper introduces the concept of human-LLM archetypes, defined as re-occurring socio-technical interaction patterns that structure the roles of humans and LLMs in collaborative decision-making.
Conceptual contribution presented in the paper (definition and framing). Method: theoretical/conceptual description in the manuscript. Sample size: not applicable.