Bibliographic record
Abstract
Although the Bahá’í community is at the beginning of its understanding of how to apply Bahá’u’lláh’s teachings to heal the ills of the world, exciting learning has taken place regarding the development of patterns of community life and the application of Bahá’í principles to provide relief to the suffering of humanity. Still in a stage of infancy, experiments in Bahá’í-inspired social and economic development, or “social action,” have been reinforced by recent encouragement from the Universal House of Justice to engage in social action as a natural outgrowth of the maturation of community life and grassroots expressions of need. It is an exciting time to be a part of the Bahá’í community, as we are at the beginning of our learning regarding the implementation of social action as a tool for the well-being of society. This article examines the history of experience and evolution in thinking regarding social action in the Bahá’í community, focuses on the Tahirih Justice Center’s experience as one example of such learning, and critically examines the culture of service we must embody as a Bahá’í community.
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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.028 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.030 | 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".