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Record W2168681459 · doi:10.1287/orsc.1100.0576

Dormant Ties: The Value Of Reconnecting

2010· article· en· W2168681459 on OpenAlexaff
Daniel Z. Levin, Jorge Walter, J. Keith Murnighan

Bibliographic record

VenueOrganization Science · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Capital and Performance Analysis
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsInterpersonal tiesNoveltyStrong tiesSocial capitalValue (mathematics)Perspective (graphical)Public relationsPsychologyBusinessPolitical scienceSocial psychologyLawComputer science

Abstract

fetched live from OpenAlex

The social networks literature suggests that ties must be maintained to retain value. In contrast, we show that reconnecting dormant ties—former ties, now out of touch—can be extremely useful. Our research prompted Executive MBA students to consult their dormant contacts about an important work project; outcomes compared favorably to those of their current ties. In addition, reconnecting previously strong ties led to all of the four benefits that are usually associated with either weak ties (efficiency and novelty) or strong ties (trust and shared perspective). These findings suggest that dormant relationships—often overlooked or underutilized—can be a valuable source of knowledge and social capital.

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)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.005
Scholarly communication0.0060.007
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.009
GPT teacher head0.211
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2010
Admission routes1
Has abstractyes

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