MétaCan
Menu
Back to cohort
Record W2907606008 · doi:10.3390/ani9010016

Compassionate Conservation: Exploring the Lives of African Wild Dogs (Lycaon pictus) in Botswana

2019· article· en· W2907606008 on OpenAlexafffund
Valli-Laurente Fraser-Celin, Alice J. Hovorka

Bibliographic record

VenueAnimals · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsYork UniversityUniversity of Calgary
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Guelph
KeywordsScholarshipAgency (philosophy)SubjectivityWildlifeAnimal welfareSentienceEnvironmental ethicsWildlife conservationSociologyWildlife managementEcologyPolitical scienceSocial scienceBiologyEpistemologyLaw

Abstract

fetched live from OpenAlex

This paper argues for a more compassionate conservation by positioning animals as subjects in research and scholarship. Compassionate conservation is a multidisciplinary field of study that broadly attends to the ethical dimensions of conservation by merging conservation biology and animal welfare science. However, animal geography is rarely discussed in the compassionate conservation scholarship despite sharing similar tenets. This paper argues that responsible anthropomorphism and animal geography concepts of animal subjectivity (lived experiences) and agency (capacity to act) positions African wild dogs (Lycaon pictus) as subjects in conservation research and scholarship. It merges biological research, public communication, and interview and participant observation data to present wild dogs as thinking, feeling, self-conscious animals with agency, and whose welfare is negatively affected in human-dominated landscapes in Botswana. This paper argues for more attention to be paid to animal subjectivity and agency to foster more compassionate relations with wildlife. It argues that positioning animals as subjects in research and scholarship is an ethical starting point for moving compassionate conservation forward. This ‘enriched’ scholarly approach moves us closer to appreciating the lives of wildlife and the complexity of their circumstances and experiences.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.154
Threshold uncertainty score0.990

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)0.0010.000

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 head0.065
GPT teacher head0.318
Teacher spread0.252 · 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 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

Citations18
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueAnimalsSame topicGeographies of human-animal interactionsFrench-language works237,207