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Record W2228302309

Action Research in science and practice: industrial period

2015· article· en· W2228302309 on OpenAlexaboutno aff
Yury Zhukiv

Bibliographic record

VenueOrganizational Psychology · 2015
Typearticle
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsnot available
Fundersnot available
KeywordsAction researchProductivityPeriod (music)Task (project management)Process (computing)Engineering managementManagementOperations managementEngineeringSociologyComputer scienceEconomicsEconomic growth
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this paper is to describe the history and methodology of the so-called “industrial” period of implementation of the Action Research Method (ARM). Employment of this method allows the researcher to solve a significant practical task and to make a contribution to science at the same time. Industrial period originated from the “field experiments” (Harwood studies), carried out in the K. Lewin’s group in US in the 1940s. The core idea of these research projects was “put the knowledge from the laboratory into real life”. Five projects were aimed at the analysis of group processes, the effects of group decision-making, the building of self-management systems, the training of line managers. The continuation of the industrial period was research projects carried out by TavistockInstitute of Human relations (UK). One of these projects (Glasier Project) was aimed at the analysis of group relations at all hierarchical levels in the private engineering company. Second, Haighmoor Project was aimed at the exploration of implementation process of innovative mining technology, allowing to reach significant growth of productivity in the coal industry without additional investments. Another notable research project of this period was the Ahmedabad (India), during which has been successfully carried out the transition from the conveyor to the production through self-managed work teams. For a long time, the center of the Action Research method was the Tavistock Institute in London. During the implementation of projects in the coal, metal and textile industry has been created and tested the concept and methodology of the ARM. The end of the twentieth century was marked by the expansion of geography and areas of the ARM application. Number of studies and projects applying the ARM methodology grew both in the UK and continental Europe as well as in the US, Canada and Australia.There was significant growth of research in different industries in those countries where has launcheda powerful movement for improving the quality of working life (Germany, Austria and the Benelux countries). However, in the beginning of the XXI century there has been an increase of ARM projects in education and medicine, and a decrease of traditional industrial ARM projects.

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)0.061
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.061
Threshold uncertainty score0.323

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0610.049
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.007
Science and technology studies0.0070.062
Scholarly communication0.0190.018
Open science0.0020.012
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.0070.001

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 head0.757
GPT teacher head0.620
Teacher spread0.137 · 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 designNot applicable
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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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