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Record W2093401192 · doi:10.1080/01580370701628474

Theories and methods for research on informal learning and work: towards cross-fertilization

2008· article· en· W2093401192 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 · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Education and Learning Practices
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsConceptualizationSituatedSociologyWork (physics)Dominance (genetics)EpistemologyEthnographyInformal learningSocial sciencePedagogyComputer scienceArtificial intelligenceAnthropology

Abstract

fetched live from OpenAlex

The topic of informal learning and work has quickly become a staple in contemporary work and adult learning research internationally. The narrow conceptualization of work is briefly challenged before the article turns to a review of the historical origins as well as contemporary theories and methods involved in researching informal learning and work. I review leading theoretical models by Livingstone, Eraut and Illeris, and summarize established methods in terms of case study, ethnographic and interview approaches, survey approaches and situated micro-analytic approaches. I argue that no single theoretical model or methodological approach has yet established dominance, and that these models and methods largely speak to distinctive, not wholly incompatible, features of the phenomena in question. I argue this suggests the potential for cross-fertilization of ideas is high.

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)0.007
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.426
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.292
GPT teacher head0.629
Teacher spread0.337 · 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