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Record W3088485993 · doi:10.1108/ijwhm-09-2019-0112

Creation of an OHS knowledge portal: an action research

2020· article· en· W3088485993 on OpenAlexaff
Éléna Laroche, Marie-Josée Patoine

Bibliographic record

VenueInternational Journal of Workplace Health Management · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsUniversité TÉLUQ
Fundersnot available
KeywordsKnowledge managementDocumentationProcess (computing)Context (archaeology)Knowledge sharingComputer scienceAction (physics)Knowledge transferAction researchProcess managementBusinessSociologyPedagogy

Abstract

fetched live from OpenAlex

Purpose Research findings stress the importance of adapting prevention mechanisms to the contexts experienced in the workplace. This paper presents the development and implementation of a knowledge portal that includes a range of Internet-based resources to support the prevention measures implemented by occupational health and safety (OHS) union delegates. It describes the process used to develop a knowledge portal that takes into account the needs of communities and unions as well as the constraints expressed. Design/methodology/approach The approach chosen for this project was action research, in which data collection results in various readjustment loops that allow for reflection and situational assessment. Data were collected from documentation, meetings, questionnaires and focus groups. The readjustment loops led to the implementation of a solution based on sustainability. Findings After studying the context, needs and constraints, the results suggest that for a knowledge portal to stand out, it must be consistent with classroom training, include a pedagogical approach that facilitates the transfer of knowledge, be interesting to all workers, be able to adapt to the characteristics of users and use technologies that reach across time, space and connection tools. Originality/value This knowledge portal is the result of interactions and collaborations between the university and the community, an interesting way to develop a solution. It sheds light on the fact that the action research process needs to be documented throughout the process and creation cycles in order to facilitate the sharing of the results obtained.

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 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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.850
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.223
GPT teacher head0.527
Teacher spread0.304 · 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 teacher head, 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".

Quick stats

Citations5
Published2020
Admission routes1
Has abstractyes

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