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Record W2124149848 · doi:10.1017/s0030605311000779

Attitudes towards carnivores: the views of emerging commercial farmers in Namibia

2012· article· en· W2124149848 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

VenueOryx · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsConcordia University
FundersPanthera
KeywordsCarnivoreHuman–wildlife conflictLivestockGeographyEcologyAgroforestrySocioeconomicsPredationBiologyWildlifeEconomicsForestry

Abstract

fetched live from OpenAlex

Abstract The emerging commercial farmers in Namibia represent a new category of farmer that has entered the freehold farming sector since Namibia's independence in 1990. Several assessments of agricultural training needs have been carried out with these farmers but the issue of human–carnivore conflict has not yet been addressed. This study investigated one of the key components driving human–carnivore conflict, namely the attitudes of these farmers towards carnivores and how this affects the level of conflict and carnivore removal. We observed that the attitudes of these farmers are similar to farmers elsewhere. In general, farmers reported high levels of human–carnivore conflict. Many farmers perceived that they had a carnivore problem when sighting a carnivore or its tracks, even in the absence of verified carnivore depredation. Such sightings were a powerful incentive to prompt farmers to want to take action by removing carnivores, often believed to be the only way to resolve human–carnivore conflict. Nonetheless, our study showed that farmers who understood that carnivores play an ecological role had a more favourable attitude and were less likely to want all carnivores removed. We found that negative attitudes towards carnivores and loss of livestock, especially of small stock, predicted actual levels of human–carnivore conflict. Goat losses additionally predicted actual carnivore removals. We discuss the implications of our findings in relation to the activities of support structures for emerging commercial farmers in Namibia.

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 score0.014
Threshold uncertainty score1.000

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 head0.029
GPT teacher head0.279
Teacher spread0.250 · 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