Examining partnerships in amateur sport : the case of a Canadian national sport centre
Bibliographic record
Abstract
This study explored the dynamics, challenges, and complexities encountered in forming, managing, and evaluating the interorganizational relationships of a nonprofit organization and its partners in the public, nonprofit, and commercial sectors. Using a partnership process model developed from various theoretical frameworks (Kouwenhoven, 1993; Oliver, 1990; Provan & Milward, 2001; Wood & Gray, 1991), this study examined three phases of partnership relationships (i.e., formation, management, and evaluation) to gain a better understanding of the interactions among partnering organizations in Canadian sport. Qualitative research methods were employed to investigate partnerships of one National Sport Centre (NSC). Data were collected from three sources: 28 interviews, 110 organizational documents, and attendance at three organizational meetings. Interviews, relevant document passages, and field notes were transcribed and analyzed using Atlas.ti, a qualitative analysis software program. Results indicated that environmental and organizational conditions facilitated the formation of partnerships. Interdependence among organizations, presence of a broker, presence of a network, and convergence of objectives were evident. Specific reasons for partnership formation included efficiency, stability, necessity, legitimacy, reciprocity, and asymmetry. Partnership management structures and processes were central to interactions between organizations. Partners struggled to find a balance between pressures to compete and pressures to collaborate. Power imbalances, political dynamics, and control issues primarily related to resource concerns existed, and in some cases weakened the bonds among partners. Some partnerships were formalized, while others were loosely structured and primarily based on mutual trust, previous history, and personal interest. Ambiguities regarding roles and responsibilities, and 'representativeness' influenced how partners interacted and contributed to challenges in managing partnerships. Allocating resources was a prime concern for the organizations. Several levels of analysis for outcome evaluation existed. At the community level, the performance of NSC athletes at international competitions' was a key measure of success. At the network level, effective coordination of programs and services contributing to improved performances of athletes was perceived as an important measure of effectiveness. Finally at the organizational level, factors including ability to attract and retain partners, ability to remain economically viable through resource acquisition, and achieving legitimacy were all viewed as criteria to evaluate partnership effectiveness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".