REGR: 1.3.0rc behavior change with concatenating boolean and numeric columns
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---

#### Code Sample, a copy-pastable example

```python
df1 = pd.DataFrame(pd.Series([True, False, True, True], dtype='bool'))
df2 = pd.DataFrame(pd.Series([1,0,1], dtype='int64'))

new_df = pd.concat([df1,df2]) # dtype changed from int64 to object
assert new_df[0].dtype == 'object'
```

#### Problem description

Previously, the `concat` call would produce a series with dtype `int64`, converting the bools to 1s and 0s. Now, all the values are maintained, so the dtype is `object`.

#### Expected Output

I'm not sure if this behavior change is expected or not, but I didn't see anything in the release notes that made me think it was expected, so I'd expect the result to allow `assert new_df[0].dtype == 'int64'`

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : 2dd9e9ba9009a40191c0c0b96262fa3939d609f0
python           : 3.8.2.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 19.6.0
Version          : Darwin Kernel Version 19.6.0: Sun Jul  5 00:43:10 PDT 2020; root:xnu-6153.141.1~9/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.3.0rc1
numpy            : 1.20.3
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 21.1.2
setuptools       : 41.2.0
Cython           : None
pytest           : 6.0.1
hypothesis       : None
sphinx           : 3.2.1
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.3
IPython          : 7.18.1
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : 2021.06.0
fastparquet      : 0.5.0
gcsfs            : None
matplotlib       : 3.2.2
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 4.0.1
pyxlsb           : None
s3fs             : None
scipy            : 1.6.3
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : 0.53.1

</details>
