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Record W2191524867 · doi:10.5539/hes.v6n1p1

Expanding Higher Education in Taiwan: The Case of Doctoral Education

2015· article· en· W2191524867 on OpenAlexvenueno aff
Chen-Wei Chang, Wang-Ching Shaw

Bibliographic record

VenueHigher Education Studies · 2015
Typearticle
Languageen
FieldHealth Professions
TopicDoctoral Education Challenges and Solutions
Canadian institutionsnot available
Fundersnot available
KeywordsHigher educationGovernment (linguistics)EliteEconomic growthPolitical sciencePublic relationsPrivate sectorSociologyPublic administrationEconomicsPolitics

Abstract

fetched live from OpenAlex

<p>Higher education expansion is not a new development in the world. Different countries have faced various contexts and factors that push the expansion to occur. Since 1996, the Taiwanese government has allowed the private sector to open new higher education institutions or be upgraded for open more access at the higher education level to correspond to the general public’s educational expectations. This article starts by describing the expansion of higher education from the elite to universal stage both globally and locally. The article then specifically introduces the case of the doctoral manpower structure in Taiwan and lists three specific scenarios regarding local PhDs’ reality in the current competitive job market, highlighting the further talent fault crisis in society today. In addition to discussing the consequences and challenges at the doctoral level of talent cultivation, the article further identifies the main issues facing the current manpower planning in Taiwan. The article calls for all stakeholders of the agenda to rethink the purpose of doctoral manpower cultivation in Taiwan over the long run.</p>

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.310
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.447
GPT teacher head0.603
Teacher spread0.156 · 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.

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

Citations11
Published2015
Admission routes1
Has abstractyes

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