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Record W3121659536

Political Model of Social Evolution

2011· article· en· W3121659536 on OpenAlexaff
Daron Acemoğlu, Georgy Egorov, Konstantin Sonin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicOpinion Dynamics and Social Influence
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsDemocratizationAuthoritarianismPoliticsEconomicsEconomic systemPower (physics)Set (abstract data type)DemocracyShock (circulatory)Political scienceComputer scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

Almost all democratic societies evolved socially and politically out of authoritarian and nondemocratic regimes, often as a result of revolutionary changes, illustrating the possibility of successful social evolution following major political changes. These changes not only altered the allocation of economic resources in society but also the structure of political power. Key actors demanding and agreeing to these political changes understood and cared about their short-term consequences, but not necessarily the entire sequence of events that they would unleash. In this paper, we develop a framework for studying the dynamics of political and social change that alter the balance of power in society, thus paving the way for future changes. The society consists of agents that care about current and future social arrangements and allocations which comprise of economic as well as social elements; allocation of political power determines which groups of agents have the capacity to implement changes in economic allocations and future allocations of power. Agents are forward-looking but discount the future so that they care only a limited amount about changes in the far future. The set of available social rules and allocations at any point in time is stochastic. We show that political and social change may happen without any stochastic shocks or as a result of a shock destabilizing an otherwise stable social arrangement. Crucially, the process of social change is “contingent ” (and history dependent) in the sense that the timing and sequence of stochastic events determines the long run equilibrium social arrangements. For example, the extent of democratization may depend on how early uncertainty about the set of feasible reforms in the future is resolved.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.749
Threshold uncertainty score0.314

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.034
GPT teacher head0.271
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2011
Admission routes1
Has abstractyes

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