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Record W2006017148 · doi:10.4018/jitr.2013100101

Social Capital in Management Information Systems Literature

2013· article· en· W2006017148 on OpenAlexaff
Hossam Ali‐Hassan

Bibliographic record

VenueJournal of Information Technology Research · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsYork University
Fundersnot available
KeywordsConceptualizationSocial capitalReciprocity (cultural anthropology)SociologySocial network (sociolinguistics)Cognitive dimensions of notationsSocial relationSocial entropyKnowledge managementComputer scienceEpistemologySocial psychologySocial philosophyCognitionSocial sciencePsychologySocial mediaArtificial intelligenceWorld Wide Web

Abstract

fetched live from OpenAlex

Social capital represents resources or assets rooted in an individual’s or group’s network of social relations. It is a multidimensional and multilevel concept characterized by diverse definitions and conceptualizations, all of which focus on the structure and/or on the content of the social relations. A common conceptualization of social capital in information systems research consists of a structural, relational and cognitive dimension. The structural dimension represents the configuration of the social network and the characteristics of its ties. The relational dimension epitomizes assets embedded in the social relations, such as trust, obligations, and norms of reciprocity. The cognitive dimension is created by common codes, languages and narratives, and represents a shared context that facilitates interaction. To singular or collective network members, social capital can be a source of solidarity, information, cooperation, collaboration and influence. Ultimately, social capital has been and will remain sound theoretical grounding upon which to study information systems affected by social relationships and their embedded assets.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.995
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.010
Science and technology studies0.0020.007
Scholarly communication0.0060.006
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.026
GPT teacher head0.355
Teacher spread0.329 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2013
Admission routes1
Has abstractyes

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