Managing Collaborative Effort: How Simmelian Ties Advance Public Sector Networks
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".