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Record W2042703499 · doi:10.1108/13665620010309774

Enhancing employability: the role of prior learning assessment and portfolios

2000· article· en· W2042703499 on OpenAlexaff
Karen Romaniuk, Fern Snart

Bibliographic record

VenueJournal of Workplace Learning · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Learning Practices
Canadian institutionsUniversity of AlbertaPublic Works and Government Services Canada
Fundersnot available
KeywordsEmployabilityWorkforceWorkforce developmentPortfolioWorkplace learningProcess (computing)Work (physics)Employee developmentProfessional developmentCareer developmentBusinessKnowledge managementPublic relationsPsychologyPolitical sciencePedagogyEconomic growthEconomicsEngineeringComputer science

Abstract

fetched live from OpenAlex

Examines the role of prior learning assessment, the portfolio method specifically, in workforce development. Despite the continuous evolution of work, organizational provisions for career development have not necessarily progressed to reflect advancing demands on workers. Organizations may better enable the contemporary workforce to embrace the shift from employment to employability through encouraging enhancement of both personal and professional growth. Incorporation of the portfolio process promises to augment organizational learning and development approaches by more effectively supporting workers in taking greater responsibility for managing their own careers.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0040.005
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.010
GPT teacher head0.344
Teacher spread0.335 · 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 source (direct Gemma or distilled Codex), 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

Citations35
Published2000
Admission routes1
Has abstractyes

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