Address the default integer dtype issue for 32/64-bit Python

Closes gh-151

Author: rgommers

spec/API_specification/creation_functions.md

@@ -68,7 +68,7 @@ Convert the input to an array.
 
 -   **dtype**: _Optional\[ <dtype> ]_
 
-    -   output array data type. If `dtype` is `None`, the output array data type must be inferred from the data type(s) in `obj`. Default: `None`.
+    -   output array data type. If `dtype` is `None`, the output array data type must be inferred from the data type(s) in `obj`. If all input values are Python scalars, then if they're all `bool` the output dtype will be `bool`; if they're a mix of `bool`s and `int` the output dtype will be the default integer data type; if they contain `float`s the output dtype will be the default floating-point data type. Default: `None`.
 
 -   **device**: _Optional\[ <device> ]_
 

spec/API_specification/data_types.md

@@ -6,11 +6,10 @@
 
 A conforming implementation of the array API standard must provide and support the following data types.
 
-A conforming implementation of the array API standard must define a default floating-point data type (either `float32` or `float64`), as well as a default data type for an array index (either `int32` or `int64`).
+A conforming implementation of the array API standard must define a default floating-point data type (either `float32` or `float64`), as well as a default integer data type (`int32` or `int64`). These default data types must be the same across platforms. The default integer data type may vary depending on whether Python is 32-bit or 64-bit.
 
 ```{note}
-
-The default floating-point and array index integer data types should be clearly defined in a conforming library's documentation.
+The default floating-point and array index integer data types should be clearly defined in a conforming library's documentation. Furthermore, it must be documented whether arrays can be indexed with values larger than the largest `int32` value.
 ```