Bibliographic record
Abstract
Why a New Metric Is NeededFrom the very beginning the Seventh-day Adventist Church has had the goal to preach the Three Angels' Messages to every nation, tribe, language, and people.This focus on growth and expansion was measured by listing when the various continents and then countries were entered.The church kept track of the total number of countries where the church was actively working.Even before the church was officially organized in 1863 Adventists started work in Canada.By 1875 Adventists were also found in Switzerland and Germany.In 1890 the church had work in 22 countries, by 1900 in 56, by 1930 at the end of the Daniels and Spicer era in 126, by 1950126, by in 193 (Bauer 1982:244-247):244-247), and in 2014 Adventists were working in 215 countries (Adventist Archives 2014).Measuring the progress of Adventist Mission by listing the number of countries where work is on-going might have been an adequate mission measuring stick in the early days of Adventism, but as more and more countries were entered it lost much of its effectiveness.For example, Adventist leaders challenged those early Adventists to start work in South America, in Africa, in Asia, and then to enter countries where there was no Adventist work.However, even by 1950 Adventists were working in 83.9% of the world's countries (General Conference of Seventh-day Adventists, Office of Archives and Statistics 1950) and this only increased to 90.7% in 2014.(Adventist Archives 2014).However, while Adventists work in 90% of the world's countries, they are not working in 90% of the world's languages or people groups.Therefore, measuring Adventist Mission progress by using the number of countries in which the church is working has largely lost its motivating power and helpfulness in assessing the task remaining for the Adventist Church.
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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 | 0.008 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.013 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.007 |
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".