MétaCan
Menu
Back to cohort
Record W2784786098 · doi:10.1108/cdi-12-2016-0214

Socialization resources theory and newcomers’ work engagement

2018· article· en· W2784786098 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCareer Development International · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsUniversity of GuelphUniversity of Toronto
Fundersnot available
KeywordsSocializationWork engagementOriginalityWork (physics)Industrial and organizational psychologyProactivityPublic relationsOrganizational behaviorPsychologySocial psychologyKnowledge managementCreativityPolitical scienceComputer science

Abstract

fetched live from OpenAlex

Purpose Although work engagement has become an important topic in management, relatively little attention has been given to newcomers’ work engagement in the socialization literature. The purpose of this paper is to explain how newcomers’ work engagement can fluctuate during the first year of organizational entry and the role of organizational socialization in developing and maintaining high levels of newcomers’ work engagement. Design/methodology/approach A review of the socialization literature indicates that uncertainty reduction theory has been the basis of research on socialization tactics and newcomer information-seeking both of which function by providing newcomers with information to reduce uncertainty. Socialization resources theory is used to develop a new pathway to newcomer socialization which focuses on providing newcomers with resources during the first year of organizational entry and socialization. Findings The uncertainty reduction pathway to newcomer socialization is narrow and limited because it primarily focuses on minimizing and reducing the negative effects of job demands rather than on providing newcomers with resources that are necessary to facilitate work engagement and socialization. Practical implications Organizations can use newcomers’ work engagement maintenance curves to map and track fluctuations in newcomers’ work engagement during the first year of organizational entry and they can conduct an audit of socialization resources to determine what resources are required to develop and maintain high levels of newcomers’ work engagement. Originality/value This paper describes newcomer work engagement maintenance curves and explains how socialization resources can be used to develop and maintain high levels of newcomers’ work engagement. A model of a new pathway to newcomer socialization is developed in which socialization resources, personal resources, and job demands influence newcomers’ work engagement and socialization outcomes.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.441
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.031
GPT teacher head0.248
Teacher spread0.218 · 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