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Record W4393855787 · doi:10.1504/ijmcp.2024.137637

Disengaged: the problem of employee engagement in gig workers

2024· article· en· W4393855787 on OpenAlexaff
Rebecca Wason

Bibliographic record

VenueInternational Journal of Management Concepts and Philosophy · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsAlgoma University
Fundersnot available
KeywordsEmployee engagementEmployee resource groupsBusinessGig economyEmployee researchPublic relationsWork (physics)EngineeringPolitical scienceMechanical engineering

Abstract

fetched live from OpenAlex

The objective of this study is to examine the levels of disengagement among remotely working independent gig workers with their client teams and organisations. The researcher distributed a structured questionnaire anchored on Kahn's three facets of employee engagement to various freelancers and consultants, also known as gig workers. Based on the results of the study, the respondents were adequately engaged in the work for which they were contracted, but their level of organisational and client team engagement was lower in comparison. Additionally, many respondents felt that the management had not clearly stated the significance and purpose of their work and/or had not guided them on organisational culture and norms. Thus, many of the respondents felt excluded and were unable to form social bonds with the client team that they were working with.

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)0.008
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0060.005
Scholarly communication0.0060.003
Open science0.0010.009
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.027
GPT teacher head0.316
Teacher spread0.290 · 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 designObservational
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

Citations1
Published2024
Admission routes1
Has abstractyes

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