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Record W2114061603 · doi:10.1080/158037042000225236

Learning in portfolio work: anchored innovation and mobile identity

2004· article· en· W2114061603 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueStudies in Continuing Education · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Education and Learning Practices
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPortfolioWork (physics)Knowledge managementNarrativeFunction (biology)SociologyBusinessEngineeringComputer science

Abstract

fetched live from OpenAlex

Portfolio work has become recognized as a significant if under‐researched form of work emerging in changing work structures. This article presents findings of a qualitative study of nurses and adult educators who function as ‘portfolio professionals’, in that they contract their services to multiple employers and organizations. Proceeding from interpretive analysis of their narratives, the focus here is their learning processes, particularly in relation to innovation. It is argued that they must learn how to perform innovative work while learning and acting within innovative work. Three learning/acting processes are identified: discerning and rendering something that others understand to be innovative, mobilizing others' activities around the innovation, and anchoring or integrating the innovation within existing systems. These processes inevitably entwine portfolio professionals' identities (as innovators) and their knowledge (as innovative models). Thus they are in danger of becoming fixed or anchored along with an innovation, and an important contrary movement is slipping away and beyond the very anchors they work to render.

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.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.171
Threshold uncertainty score0.496

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.069
GPT teacher head0.454
Teacher spread0.386 · 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