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Creating an Accelerated Joint BA-MPA Degree Program for Adult Learners

2007· article· en· W2810840826 on OpenAlexaboutno aff
Jennifer M. Kohler, Robert A. Cropf

Bibliographic record

VenueJournal of Public Affairs Education · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicEvaluation of Teaching Practices
Canadian institutionsnot available
Fundersnot available
KeywordsDegree programDiversity (politics)Medical educationGraduate degreeProfessional degreePublic relationsOrder (exchange)Quarter (Canadian coin)Political sciencePsychologyBusinessMedicine

Abstract

fetched live from OpenAlex

The increase in the number of adult learners in higher education has been dramatic in recent years. However, traditional MPA programs have done little to attract and accommodate these nontraditional students. This article discusses a collaborative effort between a school for professional studies offering B.A. degrees for adult learners and a department of public policy studies offering a traditional MPA degree to create an accelerated BA-MPA degree. The accelerated degree program was designed to address the need for the undergraduate program to expand its program offerings to include graduate degrees in order to tap an unfilled market. The graduate program wanted to address the need to bolster its enrollment and to increase the diversity of its student body. The article discusses several factors that have contributed to the early success of the accelerated BA-MPA program, including institutional merger, leadership support, market need, internal support, adult student support mechanisms, streamlined application process, and program liaisons. The effort to create a new program and implement it has not been without challenges, however. Chief among these have been cultural and programmatic differences between the collaborating department and the school, including traditional versus nontraditional student populations, undergraduate versus graduate education, a business versus public and nonprofit orientation, and a quarter versus semester format.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.909
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.003
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.277
GPT teacher head0.493
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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