amavisd-new doesn't seem to get autolearn= portion of the X-Spam-Status header from spamassassin

I've been trying to get Amavis to report if the mail it's checking has been auto learned by SpamAssassin, however the Amavis X-Spam-Status header seems to make no reference to it. This result is rather important to me as I would like to script sa-learn so users can use dump folders on IMAP for mail which hasn't been, or has been incorrectly learned by SA.

I'm running these versions on a fresh install of Hardy:

amavisd-new:
  Installed: 1:2.5.3-1ubuntu3
  Candidate: 1:2.5.3-1ubuntu3
  Version table:
 *** 1:2.5.3-1ubuntu3 0
        500 http://gulus.usherbrooke.ca hardy/main Packages
        100 /var/lib/dpkg/status
spamassassin:
  Installed: 3.2.4-1ubuntu1
  Candidate: 3.2.4-1ubuntu1
  Version table:
 *** 3.2.4-1ubuntu1 0
        500 http://gulus.usherbrooke.ca hardy/universe Packages
        100 /var/lib/dpkg/status

Here is what I'm getting:

X-Spam-Status: No, score=-1.927 tagged_above=-9999 required=6.31
 tests=[AWL=0.673, BAYES_00=-2.599, SPF_PASS=-0.001]

Here is what I want (from the old mail server):

X-Spam-Status: not spam, SpamAssassin (score=-0.803, required 6,
        autolearn=not spam, AWL -0.94, FORGED_RCVD_HELO 0.14)
        ^^^^^^^^^^^^

According to all the docs I've read on Amavis/SA, Amavis doesn't alter the return values of the test results from SA.

From running Amavis in SA debug mode, I get this:

[28443] dbg: learn: auto-learn: currently using scoreset 3, recomputing score based on scoreset 1
[28443] dbg: learn: auto-learn: message score: -3.25358685446009, computed score for autolearn: 0
[28443] dbg: learn: auto-learn? ham=1, spam=6, body-points=0, head-points=0, learned-points=-2.599
[28443] dbg: learn: auto-learn? yes, ham (0 < 1)
[28443] dbg: learn: initializing learner
[28443] dbg: learn: learning ham
[28443] dbg: bayes: tie-ing to DB file R/W /var/lib/amavis/.spamassassin/bayes_toks
[28443] dbg: bayes: tie-ing to DB file R/W /var/lib/amavis/.spamassassin/bayes_seen
[28443] dbg: bayes: found bayes db version 3
[28443] dbg: bayes: learned '9e0024004b5cce00aa9767ad57fcb634239234e9@sa_generated', atime: 1215809602
[28443] dbg: bayes: untie-ing
[28443] dbg: bayes: files locked, now unlocking lock
[28443] dbg: learn: initializing learner
[28443] dbg: check: is spam? score=-3.254 required=5
[28443] dbg: check: tests=AWL,BAYES_00,SPF_HELO_PASS,SPF_PASS
[28443] dbg: check: subtests=__CT,__CTYPE_HAS_BOUNDARY,__DOS_HAS_ANY_URI,__DOS_RCVD_FRI,__DOS_RELAYED_EXT,__ENV_AND_HDR_FROM_MATCH,__HAS_ANY_EMAIL,__HAS_ANY_URI,__HAS_MSGID,__HAS_RCVD,__HAS_SUBJECT,__KAM_LOTTO3,__LAST_UNTRUSTED_RELAY_NO_AUTH,__MIME_ATTACHMENT,__MIME_BASE64,__MIME_VERSION,__MISSING_REF,__MSGID_OK_DIGITS,__MSGID_OK_HOST,__MSOE_MID_WRONG_CASE,__NAKED_TO,__NONEMPTY_BODY,__PART_STOCK_CD_F,__SANE_MSGID,__TOCC_EXISTS,__TVD_BODY,__TVD_MIME_ATT,__TVD_MIME_ATT_AP,__TVD_MIME_ATT_TP,__TVD_MIME_CT_MM

So SA seems to be doing the autolearn as expected.

Here are my config files:

Amavis 50-user:
use strict;

#
# Place your configuration directives here. They will override those in
# earlier files.
#
# See /usr/share/doc/amavisd-new/ for documentation and examples of
# the directives you can use in this file
#
$unfreeze = ['unfreeze', 'freeze -d', 'melt', 'fcat']; #disabled (non-free, no security support)
$unrar = ['rar', 'unrar']; #disabled (non-free, no security support)
$lha = 'lha'; #disabled (non-free, no security support)
$myhostname = "windy.skanes.ca";
$final_spam_destiny = D_DISCARD;
$X_HEADER_LINE = "Ubuntu $myproduct_name at $mydomain";
$sa_tag_level_deflt = -9999;
$sa_kill_level_deflt = 15; # triggers spam evasive actions
$sa_dsn_cutoff_level = 15; # spam level beyond which a DSN is not sent
$sa_auto_whitelist = 1;
$sa_spam_report_header = 1;
#
# Debugging settings
#
$sa_debug = '1,bayes,learn';
$log_level = 5;
$LOGFILE = "$MYHOME/amavis.log";
$DEBUG=1;
#
#------------ Do not modify anything below this line -------------
1; # ensure a defined return

SA local.cf:

# This is the right place to customize your installation of SpamAssassin.
#
# See 'perldoc Mail::SpamAssassin::Conf' for details of what can be
# tweaked.
#
# Only a small subset of options are listed below
#
###########################################################################

# Add *****SPAM***** to the Subject header of spam e-mails
#
# rewrite_header Subject *****SPAM*****

# Save spam messages as a message/rfc822 MIME attachment instead of
# modifying the original message (0: off, 2: use text/plain instead)
#
# report_safe 1

# Set which networks or hosts are considered 'trusted' by your mail
# server (i.e. not spammers)
#
# trusted_networks 212.17.35.

# Set file-locking method (flock is not safe over NFS, but is faster)
#
# lock_method flock

# Set the threshold at which a message is considered spam (default: 5.0)
#
# required_score 5.0

# Use Bayesian classifier (default: 1)
#
use_bayes 1

# Bayesian classifier auto-learning (default: 1)
#
bayes_auto_learn 1

# Set headers which may provide inappropriate cues to the Bayesian
# classifier
#
# bayes_ignore_header X-Bogosity
# bayes_ignore_header X-Spam-Flag
# bayes_ignore_header X-Spam-Status
bayes_auto_learn_threshold_nonspam 1
bayes_auto_learn_threshold_spam 6

Any help would be greatly appreciated as I have quite a busy mail server to retire.

Thanks,
Jonathan Skanes