MétaCan
Menu
Back to cohort
Record W3127391312 · doi:10.3389/978-2-88966-345-3

Positive Organizational Interventions: Contemporary Theories, Approaches and Applications (Special Issue)

2020· article· en· W3127391312 on OpenAlexfundno aff
Llewellyn E. van Zyl, Sebastiaan Rothmann

Bibliographic record

VenueTU/e Research Portal · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Teacher Training
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsPopularityPsychological interventionIntervention (counseling)PsychologyOrganization developmentDisciplineKnowledge managementManagement scienceApplied psychologyComputer scienceSocial psychologySociologySocial scienceEngineering

Abstract

fetched live from OpenAlex

Positive Organizational Interventions (POI) have emerged as popular mechanisms to facilitate the development and wellbeing of employees and enhance organizational performance. However, despite its popularity within the academic literature, POIs still show mixed results and fail to yield returns within practice. Various reasons for such have been proposed, ranging from poor intervention methods/design and a lack of meta-theory through to a lack of clear, descriptive intervention protocols.This Special Edition aims to address contemporary approaches towards the development, implementation and evaluation of POIs which could easily be translated into practical, viable instruments for others to employ. Specifically, we call for:1. Theoretical approaches to positive organizational capacity development2. POI designs, methodologies, evaluation methods and intervention protocols3. Evidence-based POI practices4. Multi-disciplinary approaches to POIs

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)0.011
metaresearch head score (Gemma)0.022
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: Editorial · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.006
Science and technology studies0.0010.006
Scholarly communication0.0080.006
Open science0.0020.004
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0140.003

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 head0.308
GPT teacher head0.455
Teacher spread0.146 · 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
GenreEditorial

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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueTU/e Research PortalSame topicEducation and Teacher TrainingFrench-language works237,207