Strengthening Mission through Strategy: An Analysis of the Mission-Driven Excellence Strategy
Bibliographic record
Abstract
The Office of Strategy and Research (OSR) for the Seventh-day Adventist (SDA) churches in the North America Division (NAD) is beginning to implement a new strategy that focuses on mission. The OSR designed the strategy, created tools and materials to support the churches in implementing the Mission-driven Excellence (MdX) strategy. MdX combines planning and direction that helps church leaders to think strategically. MdX is a combination of pre-events, processes, and resources combined with local church strategies toward mission. The purpose of this study was to suggest strengths and improvements to the Mission-driven Excellence (MdX) strategy by seeking to better understand how the participants in the NAD pilot churches perceived the MdX strategy through its strengthens and weaknesses, and how it could be improved. This study used a qualitative method design and formative research methodology to focus on what worked well, what did not work well, and gathered suggestions for improvement on the MdX phenomena. The study’s population is found within the 67 pilot churches involved with the MdX implementation in the NAD. Thus, the population for this study is the pastors and selected church leaders within the 67 pilot churches who participated in leading the implementation of the MdX strategy at their local church. The sample involved six of the 11 pilot churches in the Ontario Conference of the Seventh-day Adventist Church (SDA) in Canada. The study found that MdX, besides being a unique NAD and SDA strategy, was also a step-by-step strategy that provides clear direction to the churches focusing on goals versus outcomes. Participants urged that MdX should not be optional and should provide more training for the leaders. Among many improvements suggested, three of them were (a) to improve the MdX materials, (b) to make [MdX] simpler by simplifying the language as well as by instead of ten, no more than five habits in total, and (c) to improve the kind of leadership the MdX needs. The MdX strategy can be used by any church as a model or tool for implementing their local strategies. As a theoretical strategy, MdX needs to be periodically re-evaluated to maintain the theory’s relevancy, refinement, and improvement.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".