Quantifying collaboration using Himmelman ' s strategies for working together
Bibliographic record
Abstract
Purpose – Coordinated school health programs (CSHPs), a type of health promoting school (HPS) program adopted by Canada and the USA, were developed to provide a comprehensive approach to school health in the USA. Community partnerships are central to CSHP and HPS efforts, yet the quality of collaboration efforts is rarely assessed. The purpose of this paper is to use Himmelman’s strategies for working together to assess the types of partnerships that are being formed by CSHPs and to explore the methodological usefulness of this framework. The Himmelman methodology describes four degrees of partnering interaction: networking, coordinating, cooperating, and collaborating, with each degree of interaction signifying a different level of partnership between organizations. Design/methodology/approach – Data were collected as part of the 2008-2009 and 2009-2010 CSHP annual Requests for Proposal from all 131 public school systems in Tennessee. Thematic analysis methods were used to assess partnerships in school systems. Descriptive analyses were completed to calculate individual collaboration scores for each of the eight CSHP components (comprehensive health education, physical education/activity, nutrition services, health services, mental health services, student, family, and community involvement, healthy school environment, and health promotion of staff) during the two data collection periods. The level of collaboration was assessed based on Himmelman’s methodology, with higher scores indicating a greater degree of collaboration. Scores were averaged to obtain a mean score and individual component scores were then averaged to obtain statewide collaboration index scores (CISs) for each CSHP component. Findings – The majority of CSHPs partnering activities can be described as coordination, level two in partnering interaction. The physical activity component had the highest CISs and scored in between coordinating and cooperating (2.42), while healthy school environment had the lowest score, scoring between networking and coordinating (1.93), CISs increased from Year 1 to Year 2 for all of the CSHP components. Applying the theoretical framework of Himmelman’s methodology provided a novel way to quantify levels of collaboration among school partners. This approach offered an opportunity to use qualitative and quantitative methods to explore levels of collaboration, determine current levels of collaboration, and assess changes in levels of collaboration over the study period. Research limitations/implications – This study provides a framework for using the Himmelman methodology to quantify partnerships in a HPS program in the USA. However, the case study nature of the enquiry means that changes may have been influenced by a range of contextual factors, and quantitative analyses are solely descriptive and therefore do not provide an opportunity for statistical comparisons. Practical implications – Quantifying collaboration efforts is useful for HPS programs. Community activities that link back to the classroom are important to the success of any HPS program. Himmelman’s methodology may be useful when applied to HPSs to assess the quality of existing partnerships and guide program implementation efforts. Originality/value – This research is the first of its kind and uses a theoretical framework to quantify partnership levels in school health programs. In the future, using this methodology could provide an opportunity to develop more effective partnerships in school health programs, health education, and public health.
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 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 | 0.055 | 0.119 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.017 | 0.014 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".