Explore the research · public research explorer
The 100 as a question constellation
Explore a provisional intellectual portfolio through the questions each person’s inspected work may help us test.NOT RANKED · NOT AN ADVISORY BOARD · INCLUSION DOES NOT IMPLY PARTICIPATION, ENDORSEMENT, ADVICE OR AFFILIATIONHow to read it
Nine kinds of pressure on one proposal.
Primary cluster is the canonical question family with the greatest number of distinct inspected question mappings; ties follow canonical family order. “Primary” only controls where a dot is placed; it does not mean a thinker works on just one family.Plain-language reference
Question and capability glossary
Questions are things the Internet of Value must be able to answer or survive. Capabilities are kinds of work a thinker has demonstrated. The codes are bookmarks, not scores.01Ontology and conceptual distinctions
What kind of thing is “value”: a relation, state, preference, capability, welfare judgement, signal, attribution, resource or something else?
Back to map ↑Which concepts must remain distinct: value, utility, price, welfare, wellbeing, meaning, preference, productivity and capital?
Back to map ↑Is value relative to the experiencing person, observer, community or institution, or is some component claimed to be observer-independent?
Back to map ↑02Time
What role does human time play: input, scarce resource, opportunity cost, exposure, state variable, budget constraint or accounting unit?
Back to map ↑How should heterogeneous hours be compared across people, activities, skill, intensity, context, voluntariness and life stage?
Back to map ↑Under what mathematical and normative conditions can time-based value be aggregated across episodes and people?
Back to map ↑03Human state and wellbeing
Should wellbeing W be represented as a scalar, multidimensional vector, latent variable, capability set, dynamic state-space or probability distribution?
Back to map ↑What is the causal structure among physiology → affect/emotion → felt experience → cognition → habit/action → performance, and which arrows are bidirectional?
Back to map ↑What timescales, memory effects, adaptation processes and delays govern changes in wellbeing?
Back to map ↑Which effects vary by person, culture and context, and which are sufficiently stable to support generalisation?
Back to map ↑04Measurement
How would W, Vcom, or other IoV constructs be operationalised with evidence of construct validity?
Back to map ↑Do measurements remain invariant across groups, languages, cultures, contexts and time?
Back to map ↑What biases enter through self-report, observers, sensors, platforms, incentives, missing data and selection?
Back to map ↑Which latent quantities and causal parameters are actually identifiable from available observations, and how does uncertainty propagate?
Back to map ↑05Dynamics and aggregation
What are the actual state variables, stocks, flows, auxiliary variables, feedback loops and exogenous drivers?
Back to map ↑Through what mechanisms do individual states become community, institutional and economic outcomes?
Back to map ↑Where is the system boundary, which variables are endogenous, and how sensitive are conclusions to alternative boundaries?
Back to map ↑Where should we expect nonlinearities, thresholds, tipping behaviour, hysteresis, path dependence and adaptation?
Back to map ↑06Economics and capital
How does IoV’s concept of value relate to utility, welfare, capabilities, revealed preference and subjective wellbeing?
Back to map ↑How should non-market work, care, public goods, commons, externalities and relational value enter the model?
Back to map ↑What precisely is the mechanism through which human/social value becomes economic or financial capital, and where might that conversion be a category error?
Back to map ↑How do inequality, ownership, bargaining power and institutional rules affect who creates, measures and captures value?
Back to map ↑07Institutions, power and protocol design
Who gets to define metrics, weights, thresholds and rules, and through what process can those decisions be contested?
Back to map ↑How does the system resist metric gaming, surveillance, coercion, discrimination and capture once measurements affect incentives?
Back to map ↑Can a protocol remain robust in the presence of strategic behaviour, plural values, asymmetric information and changing incentives?
Back to map ↑08Computation and model validation
Which model family is justified for each IoV proposition: System Dynamics, ABM, causal model, network model, state-space model, optimisation/game model or hybrid, and why?
Back to map ↑What data parameterise or calibrate the model, how well does it reproduce relevant behaviour, and when should it outperform competing models out-of-sample?
Back to map ↑Does the model pass structural, dimensional, extreme-condition, sensitivity, uncertainty and participatory validation tests?
Back to map ↑09Epistemology and reproducibility
What observations, interventions or competing findings would falsify, or materially weaken, each major IoV proposition, including VC = W × Vcom?
Back to map ↑Can an independent group inspect provenance, reproduce the analysis, fork the model, rerun it under different assumptions and publicly document disagreement?
Back to map ↑The 22 capabilities
Systems framing & boundary critique
Defines purposes, boundaries, endogenous and exogenous variables, actors, scales and alternative framings.
Back to map ↑Dynamics, feedback & control
Reasons about stocks, flows, feedback, delays, stability, adaptation, path dependence and control.
Back to map ↑Mathematical formalisation
Converts propositions into variables, functions, equations, constraints and explicit assumptions.
Back to map ↑Computational & simulation modelling
Builds and interrogates SD, ABM, discrete-event, state-space and other computational models.
Back to map ↑Causal inference & identification
Distinguishes association from intervention effects, including confounding, counterfactuals and identification.
Back to map ↑Statistical inference & uncertainty
Estimates parameters, uncertainty, heterogeneity and model error, with sensitivity and robustness analysis.
Back to map ↑Measurement, psychometrics & construct validity
Defines constructs and assesses validity, reliability, invariance, response bias and measurement error.
Back to map ↑Computational empiricism, provenance & reproducibility
Creates inspectable data and code pipelines, versioning, documentation and reproducible analyses.
Back to map ↑Multilevel aggregation, scaling & emergence
Explains conditions for individual aggregation and nonlinear macro-level emergence.
Back to map ↑Economics, value & welfare
Understands utility, welfare, capabilities, prices, non-market value, distribution and theories of value.
Back to map ↑Finance, capital & systemic risk
Understands capital formation, assets, financial networks, leverage, contagion and systemic risk.
Back to map ↑Institutions, governance & political economy
Models rules, collective action, power, incentives, state capacity, governance and distributional conflict.
Back to map ↑Network science & collective dynamics
Analyses topology, diffusion, contagion, centrality, communities and social influence.
Back to map ↑Complexity & agent-based reasoning
Works with heterogeneous agents, adaptation, non-equilibrium processes and evolutionary emergence.
Back to map ↑Decision science, optimisation, games & mechanism design
Designs decisions and rules under constraints, uncertainty, incentives and strategic behaviour.
Back to map ↑Technology, computation & AI systems
Understands platforms, AI, computational architectures, algorithms and human-technology feedback.
Back to map ↑Neuroscience, cognition & affect
Understands physiological, neural, cognitive, emotional and embodied processes.
Back to map ↑Behavioural science & human decision-making
Studies preference, habit, learning, bias, motivation, influence and decision behaviour.
Back to map ↑Wellbeing & human development
Understands subjective wellbeing, flourishing, mental health, capabilities and human-development measurement.
Back to map ↑Ethics, philosophy of science & epistemology
Separates descriptive and normative claims, examines evidence and limits of quantification.
Back to map ↑Participatory, qualitative & field-based systems inquiry
Integrates stakeholder knowledge, field observation, qualitative evidence and competing perspectives.
Back to map ↑Protocol, institutional & policy design / implementation
Converts insights into rules, protocols, organisations or policy and evaluates implementation feedback.
Back to map ↑Accessible index