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Record W2994702046

The Problem of the Skills Gap Agenda in Canadian Post-Secondary Education.

2019· article· en· W2994702046 on OpenAlexaffabout
Melody Viczko, Jenna R. Lorusso, Shannon McKechnie

Bibliographic record

VenueScholarship@Western (Western University) · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Education and Societal Dynamics
Canadian institutionsWestern University
Fundersnot available
KeywordsSubject (documents)RestructuringPoliticsRepresentation (politics)DemocracySociologyRationalityDiscourse analysisSet (abstract data type)Space (punctuation)Neoliberalism (international relations)Public relationsPolitical sciencePublic administrationPolitical economyLaw
DOInot available

Abstract

fetched live from OpenAlex

The mismatch between graduates’ skills and the needs of the labour market is a continuing discourse in Canada and on a global scale. Yet, arguments on how to restructure PSE are not united. Given these competing discourses, we ask the following research questions: What should we make of the various representations of the skills gap, and how are contemporary PSE students positioned in this discursive space? We use Bacchi’s problem representation approach to policy analysis to examine four policy actors’ statements influencing Canadian PSE to examine the discourses surrounding the perceived skills gap in Canadian PSE. We argue that, while these policies call for disparate PSE reforms, they are all underpinned by the same neoliberal rationality. The different calls for reform reflect a harmonized and complementary set of discourses that reify PSE students as a single subject—a one-dimensional, homogenous, economic subject, devoid of difference. We suggest discourses that position PSE students as political actors in determining their education and roles in a democratic society are needed.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.879
Threshold uncertainty score1.000

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 communication0.0000.001
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 head0.044
GPT teacher head0.324
Teacher spread0.280 · 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 designObservational
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

Citations4
Published2019
Admission routes2
Has abstractyes

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