Peer review of: Kea show three signatures of domain-general statistical inference (2020)



 

Reviewers' Comments: 
 
Reviewer #1: 
Remarks to the Author: 
The authors have addressed most of my previously expressed concerns and I agree with the overall 
conclusion that kea have demonstrated a capacity for statistical inference and that kea are able to 
consider information from different domains when drawing statistical inferences. However, I still have 
some issues with the terminology used by the authors (see below). 
 
 
My main criticism was that the design of the study differed from previous studies testing human 
infants and non-human primates in various ways. Most importantly, I was concerned that the large 
number of trials within each condition, the “training until reaching criterion”, the (not 
counterbalanced) order of conditions, and the fact that not all conditions used novel populations of 
tokens might have facilitated associative learning and, therefore, that keas´ performance might not 
reflect true statistical abilities. 
The authors have now added information about first trial performance to the manuscript. This 
information shows that kea did in fact prefer the “correct” sample from the first trial onwards in all 
conditions. Moreover, the authors conducted additional analyses showing that subjects´ performance 
did not improve over trials within conditions, neither did it improve across conditions. Hence, it seems 
unlikely that the birds used associative learning mechanisms to solve the tasks. 
 
In my last revision I wrote: “However, given the methodological discrepancies between the present 
study (several hundreds of trials per condition, using the same population across conditions) and 
primate studies (12 trials per condition, different populations for each condition), I think it is 
misleading to conclude that kea, but not monkeys, succeeded in statistical inference tasks in which 
absolute and relative frequencies were disentangled”. 
The authors responded by stating that: “In regard to the differences in methods, we followed past 
methodologies in terms of the design of our experiments, and in terms of the same individuals taking 
part in several conditions (Rakoczy et al. 2014; Tecwyn et al. 2017; Eckert et al. 2018a, 2018b; Placì 
et al. 2018, 2019). We are not aware of any studies on intuitive statistics in primates where new 
participants were used for each of the different conditions.” 
There seems to be a misunderstanding here. With “different populations” I referred to the populations 
of tokens used across conditions, and emphasized that the authors risked that their birds would solve 
the tasks by means of associative learning when using the same population in several conditions. The 
authors apparently thought that I was criticizing them for testing the same population of kea across 
experiments. This was not my intention. I am aware of the fact that it is nearly impossible to have 
enough testable individuals in order to conduct a similar study using a between-subjects design for 
most species. I also don´t think that this is necessary, as long as associative learning is sufficiently 
controlled for. 
I am satisfied with the new first trial data/analysis and to me this sufficiently addresses my associative 
learning concern. 
 
I also appreciate that the authors tuned down their conclusions regarding differences between 
monkeys and kea and now acknowledge the discrepancies in study design in the discussion. 
 
 
In my last revision I wrote that, in my opinion, what keas do in this study is not integrating different 
sources of information with statistical inference, but rather flexibly deciding which of two sources of 
information will determine the outcome of the event. The authors responded by stating that the term 
‘integration’ is commonly used in the intuitive statistics literature in similar studies. To support their 

claim the authors cite three papers by Denison and Xu: Xu & Denison, 2009; Denison & Xu, 2010; 
Denison et al., 2014. 
However, the very same authors state in a review with regard to both the barrier experiment by 
Teglas et al., 2007 (after which the current Experiment 2 was designed) and the experimenter bias 
experiment by Xu and Denison, 2009 (after which the current Experiment 3 was designed): 
“In Teglas et al. (2007) and Xu and Denison (2009), infants were able to assess when to use ratio 
information and when to use domain-specific knowledge regarding naïve physics or naïve psychology 
to make an inference. These abilities are impressive as infants used very subtle cues- the presence or 
absence of a physical barrier and an agent´s perceptual access to a scene- to infer whether or not 
they should compute probabilities or instead make a judgement using physical or psychological 
knowledge, respectively. However, these experiments did not require infants to fully integrate domain-
specific knowledge in statistical inference- that is, infants were required to use one knowledge source 
or the other but not both simultaneously.” (Denison & Xu, 2012, p.41). 
In order to convincingly demonstrate that infants truly integrate, e.g. statistical and physical 
information, different task setups were used (see Denison et al., 2014; Denison & Xu, 2010; Teglas et 
al., 2011). 
 
Therefore, I am still not convinced that the current study shows that kea can integrate statistical and 
other types of information. This does not devalue the results; I think it is extremely impressive that 
kea a) are capable of statistical inference and b) can flexibly decide which of different factors is the 
important one regarding the outcome of an event. 
 
Another terminology issue arises from the word “preference” which the experimenters use with regard 
to the experimenters´ choice biases in Experiment 3. Attributing preferences or desires to others does 
imply “theory of mind”-like abilities, something that has not been addressed in this study. We cannot 
disentangle whether the birds attributed a preference for one type of token to the biased 
experimenter, or whether they merely noticed that this experimenter, for whatever reason, always 
sampled one type of token. 
Previous work on infants and chimpanzees has administered additional experiments in which subjects 
adjusted their choice when dealing with a biased experimenter depending on whether this 
experimenter had visual access to the populations or sampled blindly. Such an experiment is missing 
in the current study, therefore we cannot draw any conclusions about an attribution of mental states 
by kea. 
Hence, I think it would be more appropriate to use the term “bias” instead of “preference” throughout 
the manuscript. 
In line 243 the authors write about “social preferences”. This term usually refers to differences in 
degrees of altruism, fairness, reciprocity, etc. I believe that the authors mean “preferences of others” 
(which, again, should more accurately be “others´ choice biases”). 
 
 
 
Reviewer #2: 
Remarks to the Author: 
The authors have clarified many parts of the text and solved most of the difficulties in the earlier 
version. 
I still have differences with (or perhaps just don’t understand) their interpretation of what they mean 
by “quantity heuristics “ and “making inferences about uncertainty [that] involves generating logical 
predictions about future events based on limited information”. 
Suppose that, using conventional psychological terminology, a subject faces a mixture of S+ and S- 
stimuli, encountered sequentially in a random order, in a given proportion. Say that the subject keeps 
a running average with a recency discounting process, as in the ‘linear operator’ literature on choice 

derived last century from the Bush and Mosteller algorithms. In that case, the estimate that drives 
preference is a time-weighted function of the ratio of the two kinds of stimuli, not of only the absolute 
numbers of either S+ or S-. Would that be called by the authors a quantitative heuristic or true 
inference? Would they still claim that this is a rare phenomenon only known in primates? Such a 
mechanism would make BF Skinner happy and work for pigeons, rats, etc. It has been tested with 
different variants in many species. All studies examining animals’ response to probability speak to this 
concept. I fail to see the critical difference with ‘true logical inference’. 
It could be argued that in the present experiments the stimuli were encountered simultaneously rather 
than sequentially as in the Bush and Mosteller linear operator literature, but since the subjects 
somehow “counted” the coloured balls, they must have somehow treated the two kinds of stimuli as 
contributing to an estimate. Here the physical presentation of the balls in jars and the large number of 
items, made impossible for the subjects to see all balls present. 
It would appear that what the authors call a ‘simple quantity heuristic’ would be for the subject to 
neglect either S+ or S- in deriving a moving average, as this would then not represent the ratio but 
just absolute numbers of one or the other. But I see no attempt to examine how and whether the kea 
are counting. 
In summary, I try, but fail, to understand why being sensitive to a property of the mixture (say the 
‘orangeness’ they see), which is a function of the ratio, is more surprising or more sophisticated than 
counting the absolute numbers, which they would downgrade to being a heuristic. 
I am totally happy to let my comment stand as a difficulty of this particular referee in understanding 
the interpretation of ‘true inference’ rather than a definite failure of the study. The results do stand, it 
is the theoretical framing and the conclusions that I have difficulties with. 
 
Alex Kacelnik 
 
 
 
Reviewer #3: 
Remarks to the Author: 
The authors have addressed my comments satisfactorily.