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Record W2540424390 · doi:10.1057/978-1-137-40523-4_7

Action Research in the Canadian Context

2016· book-chapter· en· W2540424390 on OpenAlexaffabout
Kurt W. Clausen

Bibliographic record

VenuePalgrave Macmillan US eBooks · 2016
Typebook-chapter
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsNipissing University
Fundersnot available
KeywordsContextualizationScholarshipContext (archaeology)Action (physics)Function (biology)Action researchPolitical scienceVanguardSociologyPublic relationsGeographyInterpretation (philosophy)Computer scienceLawPedagogy

Abstract

fetched live from OpenAlex

This chapter examines the development and present state of action research in Canada and the many variations that exist in its realization. Specifically, it observes the evolution of a “grass-roots” researcher-practitioner movement to achieve widespread (yet fragmented) acceptance of action research by the late 1960s. Building on this contextualization, the chapter then reviews Canadian scholarship that has been produced on the subject and the major researchers who are presently at the vanguard of this movement. This is followed by a sampling of governmental initiatives, as well as federations and associations, whose work has promoted action research among their constituents. Finally, this chapter identifies a number of formal and informal networks that function at the bedrock level, aiding practitioners and scholars in their work. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.994
Threshold uncertainty score0.872

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.009
Science and technology studies0.0230.027
Scholarly communication0.0180.004
Open science0.0030.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0120.001

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 head0.379
GPT teacher head0.482
Teacher spread0.103 · 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.

Study designTheoretical or conceptual
DomainMethods
GenreMethods

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

Citations3
Published2016
Admission routes2
Has abstractyes

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