Methods for Assessing Inner Development: Spirituality andBeyond
Bibliographic record
Abstract
As practitioners and scholars of student affairs administration, we are committed to the development and growth of the whole student, a concept that has guided our profession since its inception (American Council on Education, 1937; American College Personnel Association & National Association of Student Personnel Administrators, 2004). Likewise, accompanying students on their journey of developing meaning and purpose has long been a foundational pillar of liberal education (Astin, 2004). We believe creating environments and conditions that enable students to focus on existential issues in their lives and discuss the Big Questions (Who am I? What can I believe in? Will my life make a difference?) (Dalton, Eberhardt, Bracken, & Echols, 2006) is one of the central purposes of college. As such, we must find means to measure and assess the inner workings of students’ lives: How do they make meaning? How do they define themselves? What is the state of their psychological well-being? What role does spirituality or religion play in their lives? How do they relate to others? However, the instruments and methods used–and the concepts and language they engender–will affect how students react and respond to assessment efforts. In the past 10-15 years, spirituality has been the term used to signify this aspect of student development, garnering much attention by postsecondary educators and administrators alike; yet the use of the term spirituality may not be appropriate for all students.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".