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Record W2760544929 · doi:10.29173/irie311

Debilidades, Amenazas, Fuerzas y Oportunidades (DAFO) en las redes sociales

2012· article· en· W2760544929 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

VenueThe International Review of Information Ethics · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Management and Innovation
Canadian institutionsnot available
Fundersnot available
KeywordsSWOT analysisConsolidation (business)RealmContingencySet (abstract data type)SociologyKnowledge managementPolitical scienceBusinessComputer scienceMarketingEpistemology

Abstract

fetched live from OpenAlex

As well as a first step in strategic planning within production realm, a SWOT analysis of a system-processproject in relationship with its environment is often carried out. Correspondingly, the different types of social networks can also be regarded as socio-technological environments used by social groups in the development of different projects; each of them with its own Strengths and Weaknesses in the use of such networks, which in turn entail generic and specific Opportunities and Threats to these groups. Furthermore, each social network, seen as a set of techniques and users, adopts forms of communication which enable/encourage the emergence, consolidation or disappearance of certain organizational models, for instance, with a different degree of horizontality, hierarchical, permeable or manipulated by the groups. These models are analyzed using organizational schemes, as particularly studied by Mintzberg who considers their design parameters and contingency factors. The paper deepens the analysis of deviations risks in the very complex systems-processes-projects which can be originated by the users of social networks – though with a high degree of uncertainty –, as well as their contribution feeding back the development of types and forms of the own social networks. Moreover, special attention is focused on synergies of different intensity in the acceleration of real changes within such social networks and their generated relationships, and particularly towards the likely creation of new systems of relations (in material and intellectual production, distribution, etc.) in all fields of economy, sociology, politics and culture.

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)0.003
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.931
Threshold uncertainty score0.951

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.005
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.062
GPT teacher head0.309
Teacher spread0.247 · 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