Evidence (16099 claims)
Search and filter individual claims pulled from the papers. Looking for a specific finding ("what's the effect on wages?"), you're in the right place. Want to compare whole outcome categories against each other instead? Use the Evidence Explorer.
The board below groups claims two ways: by broad theme (nine paper-level topics) and by outcome category (the 34 claim-level outcomes that the Explorer and Syntheses also use).
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Nine broad, paper-level topics. Click one to filter the claims below.
Adoption
20058 claims
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Productivity
17184 claims
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Governance
16099 claims
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Human-AI Collaboration
16034 claims
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Innovation
10501 claims
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Org Design
10496 claims
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Labor Markets
6444 claims
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Skills & Training
5385 claims
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Inequality
4148 claims
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Claims by outcome category
Counts by direction of finding. These are the same 34 outcome categories the Explorer compares and the Syntheses are written for. A linked row has a published synthesis.
| Outcome | Positive | Negative | Mixed | Null | Total |
|---|---|---|---|---|---|
| Other | 1820 | 479 | 278 | 1820 | 4588 |
| Organizational Efficiency | 2711 | 616 | 401 | 173 | 3922 |
| Governance & Regulation | 2075 | 886 | 459 | 246 | 3714 |
| Technology Adoption Rate | 1467 | 530 | 258 | 206 | 2488 |
| Decision Quality | 1281 | 496 | 289 | 152 | 2228 |
| Output Quality | 1227 | 447 | 207 | 138 | 2025 |
| AI Safety & Ethics | 634 | 754 | 207 | 83 | 1688 |
| Research Productivity | 826 | 241 | 114 | 422 | 1624 |
| Firm Productivity | 1052 | 154 | 163 | 66 | 1441 |
| Task Allocation | 685 | 211 | 331 | 99 | 1335 |
| Market Structure | 433 | 423 | 242 | 46 | 1150 |
| Innovation Output | 639 | 91 | 105 | 34 | 871 |
| Task Completion Time | 476 | 113 | 43 | 36 | 672 |
| Firm Revenue | 445 | 126 | 58 | 25 | 656 |
| Skill Acquisition | 364 | 119 | 109 | 34 | 626 |
| Consumer Welfare | 288 | 167 | 104 | 31 | 592 |
| Employment Level | 214 | 140 | 174 | 50 | 582 |
| Error Rate | 230 | 251 | 35 | 16 | 535 |
| Fiscal & Macroeconomic | 268 | 136 | 71 | 50 | 532 |
| Inequality Measures | 100 | 307 | 96 | 12 | 515 |
| Worker Satisfaction | 221 | 173 | 60 | 30 | 484 |
| Automation Exposure | 155 | 138 | 65 | 36 | 398 |
| Regulatory Compliance | 171 | 120 | 30 | 13 | 335 |
| Developer Productivity | 222 | 58 | 27 | 13 | 321 |
| Team Performance | 188 | 56 | 50 | 24 | 320 |
| Wages & Compensation | 146 | 104 | 46 | 16 | 312 |
| Training Effectiveness | 207 | 41 | 21 | 26 | 298 |
| Job Displacement | 23 | 153 | 52 | 4 | 232 |
| Hiring & Recruitment | 102 | 57 | 30 | 11 | 202 |
| Skill Obsolescence | 16 | 102 | 24 | 6 | 148 |
| Creative Output | 71 | 42 | 23 | 6 | 143 |
| Social Protection | 57 | 30 | 11 | 3 | 101 |
| Labor Share of Income | 29 | 42 | 24 | 2 | 97 |
| Worker Turnover | 43 | 29 | 6 | 4 | 82 |
| Industry | — | — | — | 1 | 1 |
Governance
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No single capability-sourcing route dominates under all conditions; the headline results depend on the corresponding model mechanisms.
Mechanism-knockout experiments that switch acquisition friction, absorption, open-weight cost reductions, and substitution on or off.
Waiting is relatively safe for a firm whose existing product cannot be replaced by the emerging technology, but it causes substantial value loss for a firm whose product is directly substitutable by that technology.
Agent-based model with demand-side substitution eroding the legacy revenue of non-adapters according to product exposure; stated as Proposition P4.
A one-time reduction in the cost of building generative-AI capability revives the build route primarily before the leading design has stabilized; after the dominant design is established, the effect is substantially weaker.
Agent-based model experiment varying the timing of an open-weight-style reduction in build costs relative to dominant-design formation; stated as Proposition P3.
The route by which incumbents enter generative AI depends on contractibility: firms tend to partner when the capability can be rented through an API and tend to absorb when the capability is too tacit to rent.
History-friendly agent-based simulation of incumbent sourcing choices across build, partner, acquire, absorb, and wait routes; stated as Proposition P1 and reported as a headline finding.
Educational data should be treated as an economic asset with potential negative externalities, including privacy harms and surveillance, requiring data-governance and property-rights analysis.
Normative political-economy implication drawn from the essay's analysis of platformisation and datafication; this is a proposed analytical framework rather than an empirically estimated result.
The platformisation and datafication of education are reshaping educational markets, data governance, and pedagogical practices while introducing new power asymmetries based on surveillance and data monetization.
Conceptual analysis of EdTech and platform actors, drawing on existing scholarship and contemporary developments in technology and education.
Funding mandates, international collaboration, journal prestige, and disciplinary norms are associated with systematic differences in Creative Commons license selection.
The study models categorical CC-license choice using multinomial logistic regression and examines funding-policy strength, international collaboration, subject category, and journal impact-factor percentile among 122,085 open-access articles.
Employee resistance to AI adoption is driven by fears of job displacement and skill obsolescence, and the paper argues that training programmes and transparent change management can help overcome this resistance.
Thematic synthesis and practical recommendations in the systematic literature review; the supplied text reports no employee survey sample or estimated intervention effect.
Data ownership and algorithmic control influence who receives economic rents from AI-driven value creation.
Qualitative case studies and literature synthesis focused on data rights, data dividends, ownership, and algorithmic governance.
Automation causes employment disruption in some occupations, while the net employment effect varies by sector, skill composition, and institutional context.
Synthesis of empirical studies within the review, with heterogeneity reported across sectors, worker skill compositions, and institutional settings.
Platform regulations such as transparency requirements, auditability, and algorithmic impact assessments can change the incentives and equilibrium outcomes associated with algorithmic design in news markets.
Theoretical policy implication; the article proposes evaluating such effects but does not estimate them.
High-quality journalism has public-good characteristics, while algorithmic amplification of low-quality content can generate negative externalities.
Normative and economic framing in the discussion of externalities and public goods; no welfare estimate or empirical comparison is provided.
Algorithmic ranking and recommendation can allocate attention in ways that create distributional externalities for news producers and affect demand for different types of content.
Theoretical implication for platform economics and attention markets; the article does not quantify the externalities or estimate effects.
Accountability for public knowledge is distributed across journalists, platforms, and regulators rather than being assigned to a single actor.
Theoretical account of accountability within the contested epistemic space; no observed cases or measured accountability outcomes are reported.
Editorial choices and algorithmic amplification jointly shape what audiences see, while editorial standards, algorithmic signals, and regulatory legitimacy jointly shape what audiences trust.
Conceptual decomposition of the framework into visibility and credibility mechanisms; not supported by an empirical sample.
The intersection of editorial, algorithmic, and regulatory logics forms a contested epistemic space in which visibility, credibility, and accountability are negotiated and may be stabilized or destabilized.
Theoretical framework identifying the intersection and its effects on public knowledge; no empirical validation is presented.
Journalism's epistemic authority emerges from the interaction of editorial, algorithmic, and regulatory logics rather than being produced solely within newsrooms.
Conceptual synthesis in the article's main finding; no empirical sample or causal test is reported.
Visibility-enabled metrics such as typing activity, response times, and screen time may improve measurement precision while also encouraging gaming and performative labor that inflate measured productivity without corresponding improvements in output quality.
Conceptual implication for AI economics and productivity measurement; the paper does not report a causal test or quantify the gap between measured productivity and output quality.
Digital visibility has dual and divergent effects: it can increase felt recognition and relational connection while also creating performative pressures that weaken authentic belonging.
Conceptual theorization grounded in relational cohesion theory and sociomaterial perspectives; supported by literature synthesis rather than primary empirical data.
AI-enabled recruitment is associated with a shift toward data-driven decision-making in which machine intelligence complements human expertise.
The paper's literature synthesis and qualitative examination of AI-powered recruitment practices, including chatbots, video interviews, targeted job advertisements, and predictive analytics.
The study advocates balancing automation gains with ethical safeguards and human oversight in AI-driven talent acquisition.
Qualitative exploration of AI-enabled recruitment experiences, including participants' concerns about privacy, organisational readiness, and ethical governance.
Organisational changes associated with AI adoption differ across phases of digital HR maturity.
The study interprets interview themes using Dave Ulrich's digital HR progression framework, comprising efficiency, innovation, information, and connection phases.
Ichnology is a useful testbed for formalizing inference because trace evidence is highly ambiguous: one organism can produce diverse traces, while similar traces can result from different organisms or abiotic processes.
Conceptual analysis of ambiguity in trace-based interpretation and comparison of biotic and abiotic explanations.
Realizing a required distinction may require revealing additional information, creating a tradeoff between privacy and the ability to make the required judgment.
Conceptual analysis of realization and informational repair; illustrated across institutional and automated decision contexts.
The interaction of the AI Act and GDPR creates synergies in governance and accountability but can also compound compliance burdens, producing trade-offs between reduced harms and trust on one hand and efficiency and innovation on the other.
Synthesis of the doctrinal analysis and the paper's discussion of compliance costs, trust, innovation, and regulatory interaction; no quantitative trade-off estimate is provided.
The combined regulatory regimes may induce firms to relocate activities, partition product lines, or maintain dual compliance tracks, thereby affecting the location of data processing and AI development.
Analytical inference from the interaction of extraterritorial obligations, compliance costs, and regulatory differences; no firm-level relocation data are reported.
EU rules may diffuse globally as de facto standards because firms adopt uniform EU-aligned practices to preserve market access, potentially reducing regulatory fragmentation while exporting EU norms.
Comparative legal analysis of extraterritoriality and market-access incentives, interpreted through the regulatory-governance and regulatory-capitalism literature.
Governance-by-design may shift innovation toward safer and more auditable systems, while potentially slowing time-to-market.
Theoretical and interpretive analysis of how embedded compliance requirements may affect product design and innovation incentives; no quantitative innovation or time-to-market estimate is provided.
Incorporating constitutive dynamics into matching theory implies that worker preferences and suitability may be endogenous and shaped by organizational experience rather than fully stable and observable in advance.
Theoretical implication for labor-market matching and market-design models; no equilibrium model or empirical estimate is presented.
Correspondence-based fit research is most compatible with surveys, alignment metrics, dyadic or market-matching measures, and causal estimation, while constitutive-fit research is more compatible with qualitative methods, longitudinal process tracing, and analysis of interpretation and affect.
Methodological implications derived from the distinct epistemological assumptions of the two ontologies.
The two ontologies imply different process explanations for organizational outcomes: correspondence models emphasize trait alignment leading to outcomes such as satisfaction and retention, whereas constitutive models emphasize interpretive work leading to meaningfulness and adjustment.
The article develops separate processual explanations for each ontology; the claim is conceptual rather than an estimate from observed data.
Person–organization fit research rests on two distinct ontologies: a correspondence ontology that treats fit as alignment between person and organization attributes, and a constitutive ontology that treats fit as an enacted and interpretive accomplishment.
Conceptual and theoretical synthesis distinguishing two underlying ontologies; no new empirical data are reported.
Rapid technological change in diagnostics, pharmaceuticals, and digital health is shifting which countries produce key health inputs.
Qualitative policy analysis based on observed technological diffusion and changes in production capacity.
Organizational AI acculturation can generate positive private returns while also producing negative social externalities through propagation of biased or stale practices.
Conceptual analysis of the divergence between firm-level incentives and aggregate welfare; the paper proposes studying incentive and regulatory designs rather than reporting an empirical estimate.
Digital transformation has stronger positive associations with substantive carbon disclosure components—carbon-related business practices, carbon governance, and carbon performance—than with the disclosure carrier or reporting format/channel.
Component-level regressions separating substantive content elements from the disclosure-carrier component of the multidimensional CIDQ index.
Country-level perceived corruption functions as a contextual moderator of the relationship between experience–expectation disconfirmation and review sentiment.
The study integrates expectancy–disconfirmation and institutional trust theories and applies statistical moderation tests to Booking.com review sentiment.
The broader directional relationship between home-country corruption, experience–expectation discrepancies, and review sentiment is reproduced in a separate Dubai sample, supporting generalizability across cities.
Robustness analysis using 242,541 Booking.com hotel reviews from Dubai and comparing the findings with the primary New York City sample.
Tourists from low-corruption countries show stronger emotional responses to discrepancies between their hotel experience and expectations, with sentiment amplified in both positive and negative directions.
Moderation tests examining whether home-country perceived corruption conditions the relationship between experience–expectation disconfirmation and textual sentiment in the New York City sample of 56,260 reviews.
Hallucination-detection approaches based on response dispersion can provide sample-level evidence of hallucination without access to model internals, but they cannot detect confident, consistent errors.
Formal review of reference-free, internal-state, and retrieval-alignment detection methods, including the worked example in the paper.
Coding was the only reported domain showing mild forgetting for Thomson-1.0-Large relative to its base model, while general mathematical and abstract reasoning remained within the Qwen performance level.
Authors' interpretation of cross-domain results, including coding scores of 39.9% for Thomson-1.0-Large versus 40.9% for Qwen3.5-397B and reasoning scores of 68.4% versus 66.8%.
AI enforcement may generate heterogeneous distributional effects across firms, individuals, large businesses, small businesses, and the informal sector.
Policy implication concerning differential exposure to AI-enabled tax enforcement; no distributional estimates are reported.
Automation of audit, risk-scoring, and tax-processing tasks is expected to reconfigure public-sector labor demand toward data-science and governance roles.
Economic interpretation of the likely labor-market effects of automating tax-administration tasks; no employment dataset or causal estimate is reported.
In settings where strategic and operational authority are fused, the decision to delegate tasks to AI or retain human discretion is endogenous to the GM's locus of authority.
Conceptual implication applying the locational-assumption finding to AI task allocation; it is not directly tested with AI deployment data.
AI adoption and performance in hospitality-like settings should be expected to vary across managers because blended strategic-operational roles, managerial adaptability, leadership style, and governance context can produce heterogeneous implementation choices and returns.
Conceptual implication derived from the hospitality GM framework; no direct AI adoption experiment or quantified treatment-effect estimate is reported.
The organizational context affecting GM decisions should be modeled as co-constituted by GM actions and governance structures rather than treated solely as an exogenous moderator.
Cross-domain theoretical synthesis emphasizing governance, institutional constraints, stakeholder interactions, and operational feedback loops.
Static models linking stable managerial traits to stable decisions are insufficient because the effects of GM characteristics depend on dynamic competence, situational expression of values, leadership adaptability, and recognition of gendered traits.
Thematic synthesis of studies on GM characteristics and leadership styles, used to qualify the dispositional assumption.
In hospitality, general managers often combine strategic and operational authority, so the relationship between leader characteristics and organizational outcomes is conditional on the GM's blended role.
Cross-domain synthesis of hospitality GM literature addressing the locational assumption and the convergence of strategic and operational authority.
Upper Echelons Theory does not function as a universal set of assumptions for hospitality general managers; its locational, dispositional, situational, and temporal assumptions operate as boundary conditions that require qualification in high-contact service settings.
Integrative review and cross-domain theoretical synthesis of 92 empirical and conceptual studies on hospitality general managers, covering GM characteristics, leadership styles, and succession.
Widespread adoption of similar explainable ESG models could increase herd behavior or model correlation across financial institutions, creating ambiguous systemic-risk effects.
Conceptual risk assessment in the paper's AI-economics implications; the supplied text reports no empirical test of systemic effects.
The reviewed research is methodologically concentrated in quantitative, model-centric studies, while qualitative and mixed-method research is limited.
Methodological coding in the systematic review, including analysis of research designs and evaluation approaches.