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Record W4232116762 · doi:10.24124/2013/bpgub1581

Conflict, styles of conflict resolution, stress and job satisfaction amongst veterinary healthcare workers in clinical settings

2013· dissertation· en· W4232116762 on OpenAlexafffund
Deborah L. Kalyn

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicConflict Management and Negotiation
Canadian institutionsUniversity of Northern British Columbia
FundersUniversity of Northern British Columbia
KeywordsJob satisfactionConflict resolutionPsychologyRole conflictJob stressSocial psychologyNegative correlationPositive correlationConflict managementApplied psychologyPolitical scienceMedicine

Abstract

fetched live from OpenAlex

This project looks at sources of stress and conflict, styles of conflict resolution and their outcomes in veterinary healthcare workers. An on-line survey was developed and sent to veterinary hospitals. Results included: Positive correlation between task and relationship conflict Positive correlation between conflict and avoiding, dominating and obliging styles of conflict resolution - Negative correlation between job satisfaction and stress - Negative correlation between job satisfaction and an avoiding style of conflict resolution and a positive correlation between job satisfaction and an integrating style of conflict resolution - Positive correlation between job satisfaction and intent to stay with both the current employer and the occupation. It is hoped this research can be used as a starting point to open dialogues about sources of stress and conflict, differing styles of conflict resolution and their benefits in terms of improved job satisfaction, decreased stress and intent to leave. --Leaf ii.

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)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.054
GPT teacher head0.383
Teacher spread0.329 · 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 designQualitative
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

Citations0
Published2013
Admission routes2
Has abstractyes

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