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Record W4395671623 · doi:10.1177/03128962241246679

Professionalisation of financial planning in Australia, Canada, and South Africa

2024· article· en· W4395671623 on OpenAlexaffabout
Daniel W. Richards, Chris Robinson, Gizelle D. Willows

Bibliographic record

VenueAustralian Journal of Management · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsYork University
Fundersnot available
KeywordsBusinessFinancial planFinance

Abstract

fetched live from OpenAlex

Delivery of apt financial advice to the public has become a high priority in developed countries due to the increased complexity of personal finance. Using the theory of professionalisation and qualitative interviews, we investigate the common barriers that three apex financial planning professional bodies encounter as they create a jurisdiction for Certified Financial Planners ® (CFP). We show that a sales orientation, commission-based remuneration, membership entrenchment with financial product providers and other stakeholder lobbying impede the professional bodies’ progress. However, governmental willingness to regulate financial advice, coupled with technological advances, may enable professionalisation. Our article adds to research on the professionalisation of financial planning and offers practical insights into how other bodies around the world can progress CFP’s jurisdiction. Our research differs from the published work on other professions because it is happening even as we write. JEL Classification: J44, L84, K23

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)0.005
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.142
Threshold uncertainty score0.369

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0080.006
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.055
GPT teacher head0.255
Teacher spread0.201 · 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 designQualitative
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
Published2024
Admission routes2
Has abstractyes

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