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Record W245198824 · doi:10.12794/metadc4775

A two-year college typology for the 21st century: Updating and utilizing the Katsinas-Lacey classification system.

2005· dissertation· en· W245198824 on OpenAlexfundno aff
David E. Hardy

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldComputer Science
TopicOpen Education and E-Learning
Canadian institutionsnot available
FundersIndiana Wesleyan UniversityHope International UniversityValdosta State UniversityLoma Linda UniversityUniversity of La VerneConcordia UniversityKing's College LondonBall State UniversityIndiana State UniversityRensselaer Polytechnic InstitutePurdue UniversityButler UniversityChapman UniversitySimpson Fund
KeywordsCensusStatistics educationTypologyPopulationAmerican Community SurveyDescriptive statisticsGeographyPortraitLibrary scienceComputer scienceStatisticsMathematics educationSociologyDemographyPsychologyMathematics

Abstract

fetched live from OpenAlex

This study had two primary purposes. The first goal was to bring the 1993/1996 Katsinas-Lacey two-year college classification system into the 21st century using data from the 2000 United States Census and the National Center for Education Statistics' Integrated Postsecondary Educational Data System (IPEDS) surveys for the 2000-2001 and 2001-2002 academic years. The second goal was to create a descriptive portrait of the universe of two-year, publicly controlled institutions that primarily offer the associate's degree mapped against the updated classification system and to describe and discern similarities and differences within this particular population by class and subclass in terms of multiple measurable characteristics for which IPEDS data were available. The study, based upon classification theory utilized in social science and management sciences - particularly the work of Bailey and McKelvey - assessed the efficacy of a number of other recent proposed community college classification systems, the original Katsinas-Lacey system and the revised version of Katsinas-Lacey created through the current research. It found both the original Katsinas-Lacey system and the revised version to meet the criteria for a well-made classification model. The study includes directories of all colleges and universities in the United States that offer the associate's degree with geographic, census population data, number of campuses and 2000-2001 unduplicated enrollment data for publicly controlled, two-year colleges and districts. Also included are data tables illustrating similarities and differences between colleges and districts in the three major classes and seven subclasses of publicly controlled institutions drawn from IPEDS survey data and detailed profiles of each of these institutional types - Rural, Rural Small, Rural Medium, Rural Large, Suburban, Suburban Single Campus, Suburban Multi-Campus, Urban, Urban Single Campus, and Urban Multi-Campus. The study concludes with a review of implications for policy and practice, and 25 recommendations for further research related to the revised Katsinas-Lacey classification system.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
gptno category
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
models splitAgreement compares identical category sets and study designs across arms.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.996
Threshold uncertainty score0.778

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.028
GPT teacher head0.307
Teacher spread0.279 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designQualitative · Theoretical or conceptual
Domainnot available
GenreEmpirical · Other

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

Citations21
Published2005
Admission routes1
Has abstractyes

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