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Record W2461393486 · doi:10.1057/9781137491923_15

Internship Programs of Higher Education in Taiwan: Cases from Fu Jen Catholic University

2015· book-chapter· en· W2461393486 on OpenAlexaboutno aff
Wei-Pen Tsai, Shang-Chi Gong, Mei-Tzu Chiang, Chen-Fon Lin

Bibliographic record

VenuePalgrave Macmillan US eBooks · 2015
Typebook-chapter
Languageen
FieldSocial Sciences
TopicHigher Education and Employability
Canadian institutionsnot available
Fundersnot available
KeywordsInternshipExperiential learningWork (physics)Cooperative educationGraduate educationBridge (graph theory)SociologyHigher educationExperiential educationPedagogyMedical educationEngineeringLibrary scienceManagementPolitical scienceMedicineVocational educationComputer science

Abstract

fetched live from OpenAlex

The first American cooperative education program started in 1906 at the University of Cincinnati with an enrollment of 27 students, while the first program in Canada started in 1957 at the University of Waterloo with an enrollment of 75 students (Haddara and Skanes 2007). Initially, the cooperative education program was established to bridge the gap between theory and practice in engineering education, meet new developments in industrial needs, and make university education accessible to students (Sovilla and Varty 2011). As Eames and Cates (2011) demonstrate, the experiential learning of a cooperative education/work integrated learning (coop/WIL) program can complement classroom learning, and education thereby becomes a more holistic, three-party, endeavor in which students, employers, and educational faculty work together to produce graduates that are more "work ready." Since much research highlights such programs as an effective means of developing graduate competencies (Coll and Zegwaard 2006; Todd and Lay 2011; Eames and Cates 2011; Johnston 2011), many such programs expanded very quickly around the world.KeywordsHigh Education InstitutionInternational BusinessSocial EnterpriseDisadvantaged GroupInternship ProgramThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.736
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.074
GPT teacher head0.326
Teacher spread0.252 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2015
Admission routes1
Has abstractyes

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