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Record W2141016930 · doi:10.1177/0263276405057196

Complexity, Science and the Public

2005· article· en· W2141016930 on OpenAlexaff
Cristian Suteanu

Bibliographic record

VenueTheory Culture & Society · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicComplex Network Analysis Techniques
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsMeaning (existential)Context (archaeology)Field (mathematics)EpistemologyData sciencePower (physics)SociologyComputer scienceMathematicsGeographyPhilosophy

Abstract

fetched live from OpenAlex

This article addresses complexity by selecting some of its key aspects that share a common feature: the power to change. They seem to change not only the way the world is approached by scientists, but also the way this approach, the resulting perspectives and their multiple relationships, are interpreted. These main aspects are: (1) the challenge of measurability, with an unexpected result that escapes the gravitational field of the measurability problem; (2) the meaning of reproducibility and the redrawn boundaries of scientific inquiry, with implications for the social sciences; (3) the altered expectations concerning prediction, which seem to break with a glorious tradition of unquestioned technological success; and (4) the discovery of all-embracing patterns of events that unavoidably include large events, possibly perceived as ‘crises’, which one may hope to understand and confront, rather than rule out. The resulting geography, with its new landmarks, new relationships among its elements and new means of orientation, is expected to reach the public sooner or later, even if the effect – according to complexity theory itself – cannot be foreseen in detail. All these fibres of change are considered in the context of a fresh meaning of time and of a topology dominated by network concepts.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.995
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0050.029
Scholarly communication0.0160.021
Open science0.0010.007
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0100.001

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 head0.016
GPT teacher head0.270
Teacher spread0.254 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations39
Published2005
Admission routes1
Has abstractyes

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