alterlab-docentlik-eligibility

name: alterlab-docentlik-eligibility description: "Runs a PARTIAL pre-screen of a Turkish associate-professorship (doçentlik) publication list against the ÜAK (Üniversitelerarası Kurul) Sağlık Bilimleri TABLO 10 criteria, applying the author-share rule (full; 0.8 + 0.5; lead-author half-the-rest split) and pass-fail checking the four computable minimums (≥100 total, ≥90 post-doctorate, ≥40 SCIE/SSCI article points, ≥3 lead-author Q1–Q4 articles). It deliberately does NOT emit an ELIGIBLE verdict — it lists the unmodelled mandatory minimums (TR Dizin/national article, citation, congress, teaching, per-category caps) for the user to verify. Use when the user wants to estimate doçentlik eligibility, calculate ÜAK points, or audit lead-author (başlıca yazar) requirements; resolve a journal's live TR Dizin status with alterlab-trdizin first, and compute the akademik teşvik (academic-incentive) score with alterlab-akademik-tesvik. Always verify the full live TABLO 10 — criteria change each term and differ per field. Part of the AlterLab Academic Skills suite." license: MIT allowed-tools: Read Write Edit Bash(python:*) compatibility: No API key required — pure offline PARTIAL pre-screen (stdlib Python) over a bundled, dated ÜAK criteria table; never emits an ELIGIBLE verdict; live journal-index status is delegated to alterlab-trdizin metadata: skill-author: AlterLab version: "2.0.0" last_updated: "2026-06-08" depends_on: "alterlab-trdizin (live TR Dizin status feeds scoring), alterlab-akademik-tesvik (separate incentive score)"

Doçentlik Eligibility — PARTIAL Pre-Screen Against the ÜAK Criteria

Pre-screens a candidate's publication list against the doçentlik (associate professorship) point gate set by ÜAK (Üniversitelerarası Kurul / the Inter-University Council) for the Sağlık Bilimleri (Health Sciences) field. Given a publication list with each item's index tier and author role, it applies the per-field point table, the author-share rule (paylaşım kuralı), and pass-fail-checks the four mandatory minimums it can compute from a publication list — reporting the exact shortfall on any that fail.

This is a PARTIAL pre-screen, not an eligibility decision — and it never outputs an "ELIGIBLE" verdict. The live TABLO 10 imposes several more mandatory minimums (a TR Dizin / national-article requirement, a citation minimum, a scientific-meeting minimum, an education minimum, and per-category point caps) that depend on inputs a bare publication list does not carry. The scorer lists those unmodelled minimums in every report and the best status it can return is PRESCREEN_PASS_VERIFY_REMAINING — "all computable checks pass; a human must still verify the rest against the live ÜAK source." A failed computable check returns FAIL_MODELLED_CHECK.

This is a deterministic offline tool: the same input always yields the same status. It does not decide the quality of a candidate's work — that is the doçentlik jury's role — and it does not look up a journal's live index status (use alterlab-trdizin for that, then feed the result in).

Quick Start

Am I eligible for doçentlik? Here is my publication list with indexes and author roles.
Doçentlik için yeterli puanım var mı? Yayın listem ekte (Q tier + yazar sırası ile).
Calculate my ÜAK doçentlik points for the Sağlık (Health) field.
Do I meet the ≥3 lead-author Q-article requirement, or am I short?

→ Run scripts/score_docentlik.py over the list (JSON), read the summary.verdict, then present the score breakdown, every failed computable minimum, the unmodelled mandatory minimums the user must still verify, and the verify-against-current-period disclaimer below. Never restate the PRESCREEN_PASS_VERIFY_REMAINING status as "eligible" — it is not.

CRITICAL: Verify Against the Current ÜAK Period

ÜAK republishes the doçentlik criteria each application term (başvuru dönemi), and the per-field point tables change between terms. The numbers bundled in this skill are pinned with a last_verified date in references/uak_criteria.md and reflect the Sağlık Bilimleri (Health Sciences) TABLO 10 as captured then.

Before relying on any output, the candidate MUST confirm the live criteria for their own field and term against the primary ÜAK source: https://www.uak.gov.tr/ (Doçentlik → Başvuru Şartları / criteria tables). The binding regulation is the Doçentlik Yönetmeliği (RG 15/4/2018 No. 30392), at https://www.mevzuat.gov.tr/mevzuat?MevzuatNo=24519&MevzuatTur=7&MevzuatTertip=5. Every output this skill produces ends with this disclaimer. Never present a verdict as the final official decision.

When to Use This Skill

Use it when the request is about scoring a publication list for the doçentlik point gate — total points, post-doctorate points, the lead-author Q-article minimum, or the co-author share calculation.

Does NOT Trigger

The Scoring Model

Modelled checks (the four this tool computes — all must pass)

1. Total points ≥ 100 across all scored work.
2. Post-doctorate points ≥ 90 — points earned from work published after the candidate received the doctorate / uzmanlık (doktora-uzmanlık sonrası). Pre-doctorate work still counts toward the 100 total but not toward this 90.
3. International SCIE/SSCI article points ≥ 40 — sum of post-doctorate Q1–Q4 article points (the intl_scie_ge_40 check). AHCI/ESCI/TR Dizin do not count toward this floor.
4. At least 3 lead-author Q-indexed articles — articles in a Q1–Q4 (SCIE/ SSCI, quartile-ranked) journal where the candidate is the başlıca yazar (lead author). For Sağlık, Q4 counts toward this ≥3 (verified against the live ÜAK Sağlık criteria). See the share rule for who qualifies as lead.

Passing all four returns PRESCREEN_PASS_VERIFY_REMAINING (not "eligible"). Failing any returns FAIL_MODELLED_CHECK with the exact shortfall.

Mandatory minimums this tool does NOT model — the user must verify these

The live Sağlık Bilimleri TABLO 10 also requires the following, which a bare publication list cannot supply. The scorer lists every one of them in summary.unmodelled_minimums and cannot clear them:

• National / TR Dizin articles — ≥3 ulusal makale, ≥2 in TR Dizin, başlıca yazar in ≥2 (resolve TR Dizin status with alterlab-trdizin first).
• Citation (atıf) — ≥5 post-doctorate citation points.
• Scientific meeting (bilimsel toplantı / bildiri) — ≥5 points.
• Education / teaching (eğitim-öğretim) — ≥2 points.
• Per-category point caps — thesis-derived, books, citation, project, thesis supervision, patent, award all have ceilings (values single-source — verify).

Why no ELIGIBLE verdict. Because these minimums are unmodelled, a green pass on the four computable checks is necessary but not sufficient. The tool therefore structurally cannot output "eligible" — re-verify the full TABLO 10 checklist against the live ÜAK source for the candidate's term. Full detail and provenance: references/uak_criteria.md.

Per-field point table (bundled, dated)

The point a publication earns depends on the field (alan) and the journal's index tier. This skill bundles the Sağlık Bilimleri TABLO 10 values captured on the last_verified date:

Other fields (Fen, Sosyal, Mühendislik, …) use different tables — the script accepts a field selector but only ships the verified Sağlık table. For another field, supply that field's table from the live ÜAK source; do not reuse the Sağlık numbers. Full table and provenance: references/uak_criteria.md.

Author-share rule (paylaşım kuralı)

A publication's face points are scaled by the candidate's authorship role:

• Single author → full points (×1.0).
• Two authors → the lead author (başlıca yazar) gets 0.8; the non-lead second author gets 0.5 (the two are not scored equally).
• Three or more authors → the lead author (başlıca yazar) takes half the points; the remaining half is split equally among all remaining authors.

The script computes the candidate's scaled contribution per item from the author count and the candidate's role. Worked numeric examples and the exact rounding convention are in references/scoring_rules.md.

başlıca yazar (lead author) — first author, corresponding author, or the sole supervising (advisor) author of a student-derived article, per ÜAK's definition. The candidate declares this per item; the scorer trusts the flag but reports it so a reviewer can audit it.

Pipeline (how to run it)

1. Capture the publication list

Each item needs: a title (free text), the field, the index tier (one of Q1 Q2 Q3 Q4 AHCI ESCI TRDizin), the author count, whether the candidate is lead author, and whether it is post-doctorate. Example JSON:

{
  "field": "saglik",
  "publications": [
    {"title": "Article A", "index": "Q1", "authors": 3, "is_lead": true,  "post_doc": true},
    {"title": "Article B", "index": "Q2", "authors": 1, "is_lead": true,  "post_doc": true},
    {"title": "Article C", "index": "TRDizin", "authors": 2, "is_lead": false, "post_doc": false}
  ]
}

If a journal's index tier is uncertain, resolve it first: for TR Dizin status run alterlab-trdizin; for quartile, check the candidate's records. Do not guess a tier — an unknown tier must be flagged, not scored.

2. Run the scorer

uv run python skills/turkish-academia/alterlab-docentlik-eligibility/scripts/score_docentlik.py \
    publications.json \
    --out docentlik_report.json

• The input path may be - (stdin) or inline JSON.
• --field saglik (default) selects the bundled table; other fields require a supplied table file and the script refuses to invent one.
• Omit --out to print the JSON report to stdout.

The script is pure stdlib — no network, no third-party deps — so it runs in a bare uv environment and is fully reproducible offline.

3. Read the report and present it

Parse summary.verdict (FAIL_MODELLED_CHECK / PRESCREEN_PASS_VERIFY_REMAINING — there is no ELIGIBLE value) and present:

1. The headline status and the four computable check results (total_points, post_doc_points, intl_scie_points, lead_q_articles) against their thresholds (100 / 90 / 40 / 3).
2. A per-publication table with each item's face points, the applied share factor, and its scaled contribution.
3. For every failed minimum, the exact shortfall (e.g. "82 / 100 points — 18 short" or "2 / 3 lead-author Q articles — 1 short").
4. The unmodelled mandatory minimums from summary.unmodelled_minimums as a checklist the user must verify by hand — make clear the tool could not check these and that a PRESCREEN_PASS_VERIFY_REMAINING is not an eligibility confirmation.
5. Any items with an unknown index tier, flagged as unscored.
6. The verify-against-current-period disclaimer, always.

Output Shape (excerpt)

{
  "tool": "alterlab-docentlik-eligibility/score_docentlik.py",
  "version": "2.0.0",
  "field": "saglik",
  "table_last_verified": "2026-06-08",
  "prescreen_only": true,
  "summary": {
    "verdict": "FAIL_MODELLED_CHECK",
    "verdict_meaning": "At least one modelled minimum ... fails — not eligible ...",
    "all_modelled_checks_pass": false,
    "total_points": 95.0,
    "post_doc_points": 85.0,
    "intl_scie_points": 60.0,
    "lead_q_articles": 2,
    "checks": {
      "total_ge_100":         {"pass": false, "value": 95.0, "threshold": 100, "short": 5.0},
      "post_doc_ge_90":       {"pass": false, "value": 85.0, "threshold": 90,  "short": 5.0},
      "intl_scie_ge_40":      {"pass": true,  "value": 60.0, "threshold": 40},
      "lead_q_articles_ge_3": {"pass": false, "value": 2,    "threshold": 3,   "short": 1}
    },
    "unmodelled_minimums": [
      {"id": "national_trdizin_articles", "label_tr": "Ulusal makale / TR Dizin asgari koşulu", "requirement": "...", "why_unmodelled": "..."}
    ]
  },
  "publications": [
    {"title": "Article A", "index": "Q1", "face_points": 30, "share_factor": 0.5, "scaled": 15.0, "counts_lead_q": true, "is_scie_ssci": true}
  ],
  "disclaimer": "PARTIAL PRE-SCREEN — NOT an eligibility decision. ... It therefore NEVER returns 'ELIGIBLE'. ÜAK doçentlik criteria change each application term ... verify the full TABLO 10 at https://www.uak.gov.tr/ ..."
}

The only two verdict values are FAIL_MODELLED_CHECK and PRESCREEN_PASS_VERIFY_REMAINING. There is no ELIGIBLE value by design.

Self-Check Before Reporting

• Did you state the field and the table's last_verified date? A Sağlık result must not be presented as valid for another field.
• Are all four modelled checks reported (total / post-doc / intl SCIE-SSCI / lead-author Q), even the ones that pass?
• Did you present the unmodelled mandatory minimums as a verify-by-hand checklist, and make clear the tool did NOT check them?
• Did you avoid calling a PRESCREEN_PASS_VERIFY_REMAINING result "eligible"? It is not an eligibility confirmation.
• Did any item have an unknown index tier? Those are unscored — say so, do not silently drop or guess them.
• Is the headline verdict consistent with the checks (any failed modelled minimum → FAIL_MODELLED_CHECK)?
• Did you include the verify-against-current-period disclaimer?

References

• references/uak_criteria.md — the bundled, dated Sağlık Bilimleri TABLO 10 point table, the four MODELLED minimums, the mandatory minimums NOT modelled (verify by hand), and the primary ÜAK source links.
• references/scoring_rules.md — the author-share rule with worked numeric examples, the lead-author definition, the SCIE/SSCI ≥40 floor, and the rounding convention.

Part of the AlterLab Academic Skills suite.