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Record W4360994600 · doi:10.36939/ir.202303271145

To Conserve and Protect: “Making Sense” of Conservation Officer uses of Emotional Labour

2023· dissertation· en· W4360994600 on OpenAlexaffabout
Courtney M. Dowdall

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicEmotional Labor in Professions
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsOfficerNexus (standard)Public relationsWildernessEmotional laborSocial psychologyPersonaEnforcementPsychologyPolitical scienceEngineeringLawEcology

Abstract

fetched live from OpenAlex

Given the unique role that conservation officer’s play in our society, it is critical that researchers better understand factors that may influence the activities and behaviours of the individuals tasked with dealing with complex emotions of others, ensuring the safety of Canada’s backcountry wilderness, all while maintaining a tough persona and enforcing the law (Moreto et al., 2015; Moreto, 2016). Hochschild’s (1983) concept of “emotional labour” is employed within this document to explore the extent to which conservation officers rely on their ability to deal with complicated emotions, within themselves and those of individuals they encounter. Due to the limited literature exploring the nexus between conservation officers and emotional labour, a grounded theoretical approach was selected to accommodate the emerging nature of these concepts. Identifying the driving factors in conservation officer behaviour provides avenues to better understand the feasibility, applicability, and likelihood of success when introducing policy aimed at improving officer mental health (Moreto et al., 2015). This study is based on twelve in-depth qualitative interviews and six commentated walks with members from provincial and private parks in British Columbia, Canada. Within it, I will explore how conservation officers engage in emotional labour, as well as its impact. The results reveal how managing emotions according to the organizationally mandated display rules can affect an officer’s well-being, and it highlights the need for future research to enable park enforcement organisations to deal more effectively with work-related stress.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.921
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.051
GPT teacher head0.390
Teacher spread0.340 · 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 designTheoretical or conceptual
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
Published2023
Admission routes2
Has abstractyes

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