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Record W4388223477 · doi:10.1080/02601370.2023.2267770

Continuing professional development as lifelong learning and education

2023· article· en· W4388223477 on OpenAlexaboutno aff
Andrew L. Friedman

Bibliographic record

VenueInternational Journal of Lifelong Education · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Education and Societal Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsLifelong learningContinuing professional developmentProfessional developmentContinuing educationPedagogyPerspective (graphical)Public relationsAdult educationSociologyHigher educationFocus groupPolitical scienceMedical educationMedicine

Abstract

fetched live from OpenAlex

Continuing professional development (CPD) is a substantial, but hitherto largely unappreciated component of lifelong learning and education (LLL/LLE). CPD encourages analysis of the LLL/LLE of those with high education in early years. It draws attention to the influence of particular organisations, professional associations and regulatory bodies, not only as suppliers of LLL/LLE, but also as facilitators of perpetual cycles of learning and in so doing connect lifelong learning with individual identities as professionals. This study highlights the importance of bringing a sociological perspective into understanding participation in LLL/LLE through consideration of a wider range of stakeholders. Data is presented on these organisations' CPD policies from a large-scale survey carried out in the UK triennially between 2003 and 2018, in addition to interviews, focus groups and other surveys of employees of these organisations in the UK, as well as in Australia, Canada and Ireland reported in many publications. The development path of CPD and the changes this has led to for the exercise of professionals' lifelong learning and for the functioning of these organisations themselves is analysed. CPD policies and programmes are portrayed as a structured system distinct from university continuing education and training.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.633
Threshold uncertainty score0.779

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.014
GPT teacher head0.395
Teacher spread0.381 · 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

Citations27
Published2023
Admission routes1
Has abstractyes

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