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Record W3036215329 · doi:10.21307/connections-2019.013

Embarked on social processes (the rivers) in dynamic and multilevel networks (the boats)

2020· article· en· W3036215329 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueConnections · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Strategy and Innovation
Canadian institutionsnot available
Fundersnot available
KeywordsKnowledge managementFace (sociological concept)Government (linguistics)Process (computing)SociologyPresentation (obstetrics)PoliticsEmpirical researchMultilevel modelEntrepreneurshipSocial network analysisPublic relationsData sciencePolitical scienceComputer scienceSocial capitalSocial scienceEpistemology

Abstract

fetched live from OpenAlex

Abstract This paper is the written text underlying the keynote presentation at the Sunbelt XXXVIII in Utrecht, 2018. It presents a neo-structural approach to social processes in the organizational society and the usefulness of the analyses of multilevel networks to understand how we navigate these processes and are made aware of them when we face cooperation dilemmas. Empirical illustrations look at how multilevel networks and relational infrastructures are useful to research a process such as coopetitive learning in science, business and government. A conclusion focuses on the role of multilevel relational infrastructures in institutional entrepreneurship, social change and politics, as well as on our responsibility to develop our knowledge of these social processes and multilevel relational infrastructures as open science.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.648
Threshold uncertainty score0.435

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.039
GPT teacher head0.241
Teacher spread0.202 · 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