Fierce international debates rage over whether trophy hunting is socially acceptable, especially when people from the Global North hunt well-known animals in sub-Saharan Africa. We used an online vignette experiment to investigate public perceptions of the acceptability of trophy hunting in sub-Saharan Africa among people who live in urban areas of the USA, UK and South Africa. Acceptability depended on specific attributes of different hunts as well as participants’ characteristics. Zebra hunts were more acceptable than elephant hunts, hunts that would provide meat to local people were more acceptable than hunts in which meat would be left for wildlife, and hunts in which revenues would support wildlife conservation were more acceptable than hunts in which revenues would support either economic development or hunting enterprises. Acceptability was generally lower among participants from the UK and those who more strongly identified as an animal protectionist, but higher among partic..., Data collected from an online vignette experiment hosted on the Qualtrics platform. Data analysed in R statistical software., R statistical software. Required packages called at the top of the accompanying R script., # Public perceptions of trophy hunting are pragmatic, not dogmatic

Data underpinning analyses presented in Hare et al (2024), ‘Public perceptions of trophy hunting are pragmatic, not dogmatic’.

Description of the Data and file structure

This data set includes all columns necessary to replicate model fitting, selection, and comparisons outlined in the manuscript.

Variable names mean:

• education = participant’s level of formal education
• people.animals = whether a participant would prioritise people or wild animals if their interests clash
• individuals.groups = whether a participant would prioritise individual wild animals or groups of wild animals if their interests clash
• hunter = whether a participant identifies as a hunter
• conservationist = whether a participant identifies as an advocate for environmental conservation
• animal.protectionist = whether a participant identifies as an advocate for animal protection
• human.rights = whether a participant i...

In 17th of January 2019 Troy Hunt wrote a blogpost about a data leak that was shared on late December 2018/early January 2019, named Collection #1. Upon the blog-post from Troy Hunt, a forum post in RaidForums surfaced, containing the the following statement. checked to see if anyone has performed a new analysis on the full data of all possible world universities, but to my surprise, no one attempted to analyze the new leak. As a result, I took it upon myself to perform a somewhat basic analysis of the data, analyzing the counts university official domains, country code university emails domain and also uncompleted emails (for security) etc. Source:https://arszilla.com/leak-review-reviewing-collection-1_5-and-antipublic-myr-and-zabagur-1_2

Source URL: https://web.archive.org/web/20031123133629/http://colour.derby.ac.uk:80/colour/info/catweb/
Source DOI: https://doi.org/10.1002/(SICI)1520-6378(199908)24:4%3C295::AID-COL10%3E3.0.CO;2-K

M. Ronnier Luo and Peter A. Rhodes

Colour & Imaging Institute
University of Derby
Derby
England

INTRODUCTION

A chromatic adaptation transform is capable of predicting corresponding colours. Corresponding colours are described by two sets of tristimulus values that give rise to the same perceived colour when the two samples are viewed under test and reference light sources or illuminants. The two light sources or illuminants differ in terms of their colour temperatures (or chromaticity coodinates). A chromatic adaptation transform can be effectively used for numerous industrial applications such as the evaluation of colour inconstancy for surface samples, the calculation of colour difference between pairs of samples assessed under non-daylight sources or illuminants, the provision of a colour rendering index for assessing the quality of light sources, or the prediction of coloured images across different sources or illuminants.

In October 1998, the CIE formed a new technical committee, TC 1-52, on Chromatic Adaptation Transforms during its interim meeting in Baltimore, USA with Professor M. R. Luo as its chairman. The objective of this committee is to review certain chromatic adaptation transforms with a view to making a CIE recommendation. The performance of chromatic adaptation transforms is normally evaluated using corresponding-colour experimental data sets in which each colour is defined by two sets of tristimulus values under two illuminants. Many experiments were carried out using a variety of psychophysical methods under different viewing conditions. A comprehensive collection of these data sets has been accumulated by Luo and Hunt [1] for the purposes of deriving and evaluating the CIE colour appearance model, CIECAM97s [2], and the CMC chromatic adaptation transform, CMCCAT97 [3]. The Committee has decided to make these data sets available via the Internet for public assessment. This task has been completed and the resulting database is now available via the world wide web at http://colour.derby.ac.uk. Researchers or industrialists are welcome to acquire this database for further study. This paper gives a brief description of each data set and describes the format of the data.

EXPERIMENTAL DATA SETS

Fourteen data sets have been accumulated from nine sources [4-11]: the Color Science Association of Japan (CSAJ), Helson, Lam and Rigg, LUTCHI, Kuo and Luo, Breneman, Braun and Fairchild, and McCann. Each data set includes a number of corresponding-colour pairs in which both colours in a pair appear the same when each is viewed under different viewing conditions. Table I summarises the experimental conditions in each data set including the number of phases (as defined by a set of viewing conditions), the number of corresponding-colour pairs and the viewing parameters used. The parameters considered are the light sources used for the test and reference conditions, illuminance (lux), the luminance factor of the neutral background (Y%), sample size, media and psychophysical method.

The CSAJ [4] data was divided into three sets: -C, -Hunt and -Stevens according to studies on chromatic adaptation, Hunt and Stevens effects respectively. The Helson [5], Lam and Rigg [6] data sets include corresponding colours between the test source (A) and reference source (D65). The LUTCHI [7] data includes three sets - A, D50 and WF - which are the test illuminants against a reference D65 simulator. Similarly, there are two sets for Kuo and Luo [8] data: A and TL84, which are the test light sources against a reference D65 simulator. The only data set based upon transparent media in this category is the Breneman [9] data which was divided into two sets: -C and -L according to investigations on chromatic adaptation and illuminance effects respectively. The Braun and Fairchild [10] data was accumulated by asking observers to adjust monitor colours to match those presented on reflection prints. The McCann [11] data were obtained by investigating the chromatic adaptation effect using a Mondrain figure viewed under highly chromatic test illuminants with low illuminances. Its original data was further analysed to obtain corresponding tristimulus values by Nayatani et al [12].

In total, 746 corresponding-colour pairs were gathered from experiments involving 38 phases of viewing conditions. The psychophysical methods used are haploscopic matching, memory matching and magnitude estimation.

Table I: Summary of the corresponding-colour data sets

| Data Set     | No. of Phases | No. of Samples | Illuminant |        | Illuminance(lux) | Background(Y%) | Sample Size | Medium   | Experimental Method |
|-------------------|---------------|----------------|------------|---------------|------------------|----------------|-------------|-------------|---------------------|
|          |        |        | Test    | Ref.     |         |        |       |       |           |
| CSAJ-C      | 1       | 87       | D65    | A       | 1000       | 20       | S      | Refl.    | Haploscopic     |
| CSAJ-Hunt     | 4       | 20       | D65    | D65      | 10-3000     | 20       | S      | Refl.    | Haploscopic     |
| CSAJ-Stevens   | 4       | 19       | D65    | D65      | 10-3000     | 20       | S      | Refl.    | Haploscopic     |
| Helson      | 1       | 59       | D65    | A       | 1000       | 20       | S      | Refl.    | Memory       |
| Lam & Rigg    | 1       | 58       | D65    | A       | 1000       | 20       | L      | Refl.    | Memory       |
| Lutchi (A)    | 1       | 43       | D65    | A       | 1000       | 20       | S      | Refl.    | Magnitude      |
| Lutchi (D50)   | 1       | 44       | D65    | D50      | 1000       | 20       | S      | Refl.    | Magnitude      |
| Lutchi (WF)    | 1       | 41       | D65    | WF      | 1000       | 20       | S      | Refl.    | Magnitude      |
| Kuo & Luo (A)   | 1       | 40       | D65    | A       | 1000       | 20       | L      | Refl.    | Magnitude      |
| Kuo & Luo (TL84) | 1       | 41       | D65    | TL84     | 1000       | 20       | S      | Refl.    | Magnitude      |
| Breneman-C    | 9       | 107      | D65, D55  | A, P, G    | 50-3870     | 30       | S      | Trans.   | Magnitude      |
| Breneman-L    | 3       | 36       | D55    | D55      | 50-3870     | 30       | S      | Trans.   | Haploscopic     |
| Braun & Fairchild | 4       | 66       | D65    | D30, D65, D95 | 129       | 20       | S      | Mon., Refl. | Matching      |
| McCann      | 5       | 85       | D65    | R, Y, G, B  | 14-40      | 30       | S      | Refl.    | Haploscopic     |

DATA FILE DESCRIPTION

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