MétaCan
Menu
Back to cohort
Record W2604189835 · doi:10.1177/0275074017700722

Managing Collaborative Effort: How Simmelian Ties Advance Public Sector Networks

2017· article· en· W2604189835 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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 American Review of Public Administration · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Policy and Administration Research
Canadian institutionsnot available
Fundersnot available
KeywordsPublic relationsEliteInterpersonal tiesStrong tiesWork (physics)Focus groupFocus (optics)Social network analysisKnowledge managementSociologyBusinessPolitical sciencePsychologyMarketingSocial psychologyComputer scienceEngineeringPoliticsSocial capital

Abstract

fetched live from OpenAlex

The research reported here is a structural analysis of the significance of ties to network leaders in securing the essential effort necessary to whole, goal-directed network functioning. Drawing on the work of Chester Barnard, we focus on one of Barnard’s three functions of the executive, securing essential effort and then examine the importance of certain network ties for securing effort in a goal-directed network. We specifically focus on Simmelian or mutual third-party ties to network leaders and the conditions under which those Simmelian ties are of greater significance for securing effort. Our study examines the Southern Alberta Child and Youth Network (SACYHN), a multisector publicly funded network that worked to facilitate interorganizational connections to improve child and youth health and well-being. Data were collected via an organizational questionnaire and elite interviews and were analyzed using Multiple Regression Quadratic Assignment Procedure (MRQAP). Implications are discussed for network management and leadership, for both theory and practice, focusing especially on the role of ties to network leaders in facilitating connections among member organizations working in different domains.

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)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.956
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.003
Scholarly communication0.0010.002
Open science0.0020.000
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 head0.064
GPT teacher head0.410
Teacher spread0.346 · 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