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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Innovative Techniques for Estimating Illegal Activities in a Human-Wildlife-Management Conflict
|
|---|---|
| Published in |
PLOS ONE, January 2013
|
| DOI | 10.1371/journal.pone.0053681 |
| Pubmed ID | |
| Authors |
Paul Cross, Freya A. V. St. John, Saira Khan, Andrea Petroczi |
| Abstract |
Effective management of biological resources is contingent upon stakeholder compliance with rules. With respect to disease management, partial compliance can undermine attempts to control diseases within human and wildlife populations. Estimating non-compliance is notoriously problematic as rule-breakers may be disinclined to admit to transgressions. However, reliable estimates of rule-breaking are critical to policy design. The European badger (Meles meles) is considered an important vector in the transmission and maintenance of bovine tuberculosis (bTB) in cattle herds. Land managers in high bTB prevalence areas of the UK can cull badgers under license. However, badgers are also known to be killed illegally. The extent of illegal badger killing is currently unknown. Herein we report on the application of three innovative techniques (Randomized Response Technique (RRT); projective questioning (PQ); brief implicit association test (BIAT)) for investigating illegal badger killing by livestock farmers across Wales. RRT estimated that 10.4% of farmers killed badgers in the 12 months preceding the study. Projective questioning responses and implicit associations relate to farmers' badger killing behavior reported via RRT. Studies evaluating the efficacy of mammal vector culling and vaccination programs should incorporate estimates of non-compliance. Mitigating the conflict concerning badgers as a vector of bTB requires cross-disciplinary scientific research, departure from deep-rooted positions, and the political will to implement evidence-based management. |
X Demographics
The data shown below were collected from the profiles of 33 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 13 | 39% |
| United States | 1 | 3% |
| Unknown | 19 | 58% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 22 | 67% |
| Scientists | 8 | 24% |
| Science communicators (journalists, bloggers, editors) | 3 | 9% |
Mendeley readers
The data shown below were compiled from readership statistics for 175 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 4 | 2% |
| France | 1 | <1% |
| Australia | 1 | <1% |
| Mozambique | 1 | <1% |
| South Africa | 1 | <1% |
| Brazil | 1 | <1% |
| Mexico | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 164 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 37 | 21% |
| Student > Ph. D. Student | 35 | 20% |
| Researcher | 33 | 19% |
| Student > Doctoral Student | 12 | 7% |
| Student > Postgraduate | 9 | 5% |
| Other | 26 | 15% |
| Unknown | 23 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Environmental Science | 50 | 29% |
| Agricultural and Biological Sciences | 50 | 29% |
| Social Sciences | 15 | 9% |
| Medicine and Dentistry | 8 | 5% |
| Veterinary Science and Veterinary Medicine | 6 | 3% |
| Other | 15 | 9% |
| Unknown | 31 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 42. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 April 2018.
All research outputs
#1,005,211
of 25,916,093 outputs
Outputs from PLOS ONE
#12,865
of 226,156 outputs
Outputs of similar age
#8,084
of 295,649 outputs
Outputs of similar age from PLOS ONE
#264
of 4,865 outputs
Altmetric has tracked 25,916,093 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 226,156 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.8. This one has done particularly well, scoring higher than 94% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 295,649 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 4,865 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.