Religious affiliation and hiring practice: a case study of Concordia University Irvine
Bibliographic record
Abstract
In 1976, Christ College (CC), located in Irvine, California, began offering degrees leading to positions in the Lutheran Church-Missouri Synod (LCMS). The college comprises only 1 of several departments within Concordia University Irvine (CUI). Meanwhile, CUI is part of the Concordia University System (CUS), a nationwide network of LCMS 2- and 4-year colleges. Transformation of CC into a diverse university has been accompanied by challenges. Although enrollment is up, costs have risen. And although stakeholders prefer to hire full-time faculty with ties to the LCMS, few qualified candidates fulfill this stricture. These and other threats, coupled with the economic recession, could bring CUI to cessation. Therefore, the primary purpose of this qualitative historical case study was to examine the historic hiring practice at CUI and its effect on the university's growth. Another purpose was to point to leadership positions and leadership styles that may be best suited to implementing change at CUI and seeing that change through to fruition. Using purposeful sampling, the researcher selected the Irvine campus from the 10 campuses making up the CUS, as CUI is the only campus practicing the historical hiring policy limiting full-time faculty to LCMS members. The researcher examined historical data concerning hiring practices in the CUS and specifically at CUI. Primary and secondary data sources obtained from LCMS, CUS, and CUI were analyzed using a coding process to categorize data pertinent to the study's 6 research questions. The findings of this study point to the most viable scenario for making changes in hiring practices at CUI and for leading change. Specifically, they reveal no written policy at CUI prohibiting CUI from hiring non-LCMS full-time faculty. Findings also suggest that students' academic demands are not met and may be hindered by the current hiring practices at CUI. Finally, the researcher offers recommendations for change throughout the university: changes to CC, a new hiring policy for CUI, changes at CUI based on opinion polls, a method for changing the university culture, creation of a strategic planning process, a timeline for planning, and a long-range evaluation process.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.024 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".