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Record W4221142732

Business Ecosystem: How a Scientific and Commercial Activity Survive Turbulence

2022· preprint· en· W4221142732 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2022
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Development and Digital Transformation
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsEcosystemTurbulenceBusinessEnvironmental resource managementEnvironmental scienceEcologyGeographyMeteorologyBiology
DOInot available

Abstract

fetched live from OpenAlex

The communication of scientific knowledge through the publications of scientific periodicals is organized in a complex and dynamic business ecosystem where convergent and divergent objectives coexist. The purpose of this paper is to study the cooperation strategies that ensure the maintenance and development of this business ecosystem. Our results show the coexistence of three cooperation strategies: homeostatic cooperation, pressure cooperation and adaptation cooperation. Our study provides two main contributions. First, we now have a new perspective the strategic dynamics of this business ecosystem. We have seen that the publication of scientific periodicals is an expanding community business ecosystem, through the active role of the actors in the different strata of this ecosystem. We also found that these actors can act on different cooperation strategies simultaneously. Second, the identification of three types of cooperation strategies mobilized by stakeholders is also an important contribution to the literature on business ecosystems and to the literature on cooperation strategies.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
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 score0.664
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
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 head0.029
GPT teacher head0.199
Teacher spread0.170 · 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