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Record W4200226422 · doi:10.34190/ejbrm.19.2.2510

The Learning History Methodology: An Infrastructure for Collective Reflection to Support Organizational Change and Learning

2021· article· en· W4200226422 on OpenAlexafffundabout
Julie Béliveau, Anne-Marie Corriveau

Bibliographic record

VenueThe Electronic Journal of Business Research Methods · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsUniversité de Sherbrooke
FundersCanadian Institutes of Health Research
KeywordsOrganizational learningAction researchEmpirical researchReflection (computer programming)Collective actionOrganization developmentLearning organizationAction learningOrganizational cultureKnowledge managementSociologyPsychologyPublic relationsCooperative learningPolitical scienceComputer sciencePedagogyEpistemologyTeaching method

Abstract

fetched live from OpenAlex

Organization members often complain about insufficient time to reflect collectively as they grapple with constant significant changes. The Learning History methodology can support this collective reflection. Given the scant empirical studies of this action research approach, the present paper fills this gap by giving an overview of this methodology and by presenting a qualitative study that answers the following research question: How does the Learning History methodology contribute to collective reflection among organization members during major organizational change? To answer this question, an empirical research project was led within five healthcare organizations in Canada during their implementation of the Planetree person-centered approach to management, care, and services. The data set includes 150 semi-structured interviews, 20 focus groups and 10 feedback meetings involving organization members representing all hierarchical levels in the five participating institutions. The results highlight the five types of contributions of the Learning History methodology to collective reflection within the five institutions that participated in the study: 1) a process of expression, dialogue, and reflection among organization members; 2) a portrait of the change underway; 3) a support tool for the change process; 4) a vector for mobilizing stakeholders; and 5) a source of organizational learning. The results also show how organization members’ collective reflection is built through the various stages of the Learning History methodology. By demonstrating that this collective reflection leads to true organizational learning, the findings position the Learning History as a research-action method useful both from a research standpoint and as an organizational development tool. In the conclusion, lessons learned using the LH approach are shared from a researcher’s perspective. This paper should interest researchers and practitioners who seek research methodologies that can offer an infrastructure for collective reflection to support organizational change and learning.

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)0.076
metaresearch head score (Gemma)0.106
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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.076
Threshold uncertainty score0.404

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0760.106
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0110.007
Science and technology studies0.0040.008
Scholarly communication0.0120.017
Open science0.0050.016
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0180.005

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 head0.384
GPT teacher head0.592
Teacher spread0.208 · 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
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

Citations1
Published2021
Admission routes3
Has abstractyes

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