The missing front-door question — which venue? — across the whole repository. Full
methodology + the stable venue index live in
shared-resources/journal-selection/journal-match.md
and venue-index.tsv.
Worked end to end, with real output:
worked-example.md.
Profile the paper — discipline + subfield, method/design, contribution type,
setting/data/region, ambition (be honest). Write it down once, in the shape of
paper-profile.yml;
every later skill reads the same file instead of re-deriving it.
Shortlist — run the matcher rather than reading the index by eye:
python3 tools/match_venues.py \
--title "..." --abstract "..." \
--discipline economics/labor --lane empirical --top 15
--discipline is a prior, not a filter: the discipline and its adjacents
(discipline-adjacency.tsv)
are boosted, but a strong match elsewhere still surfaces, because Step 1 is a
judgement that is sometimes wrong. Add --only-discipline when you are certain,
--exclude <venue_id> for venues that have already rejected the paper,
--json to pipe it. --list-disciplines prints the vocabulary.
Every row names where to read more — source_map for a depth pack,
profile_path for a breadth profile — and the terms it matched on, so a
nonsense hit is visible as a nonsense hit.
Read the warnings. The matcher flags weak evidence when its leading
candidates each rest on one or two shared words — a ranking built on that is
close to noise, because words the language reuses ("sensor", "generation",
"network") will out-score a genuine subject match. It flags a coverage gap
when nothing in the discipline you named scored at all: the prior can only
re-rank venues that matched, never conjure one. Either warning means do not
pass the list on as a shortlist — add the abstract, re-check the discipline
label, or report that the subject area is thin in the index and route to
rt-venue-integrity.
The matcher is measured: R@10 = 41.5% from a bare title, on a held-out half of a
1,738-paper gold set (eval/RESULTS.md).
That is a floor for one thin query, not the capability — it is why step 3 exists.
The per-discipline table there is worth reading before trusting a result: coverage is
uneven, and life sciences and natural science are visibly the thinnest.
Score each candidate on Fit × acceptance-odds × turnaround × cost/policy ×
audience, reading the live facts from each candidate's resources/official-source-map.md.
Never quote a fee, acceptance rate, turnaround or page limit from memory.
Return reach / match / safe (≈2–3 each) with one-line rationales + the live facts,
then a submit order and resubmission ladder — seed the ladder from
ladder.tsv (candidate
adjacency, not a ranking) and apply your own fit/odds judgement to it.
Cost the ladder with rt-ladder-ev whenever the
author is under a clock or is choosing between two orders. The sequence, not the
venue, is what costs a year.
*-topic-selection / *-contribution-framing.rt-venue-integrity before the author
submits somewhere unverified.【Paper profile】discipline / method / contribution / setting / ambition
【Reach】V — why; key live facts (desk-reject, turnaround, fee)
【Match】V — …
【Safe】V — …
【Submit order & ladder】V_top → if reject → V_next (what to change) → …
【Open questions】facts to re-verify in the source-map before submitting
lane — sending a qualitative/theory paper to an empirical-only venue.tier column as a precise ranking (it is an indicative bucket).