A Historiography of Settlement Archaeology in Southeast Asia, with Emphasis on the Pre-industrial State Formations | မပထနကအခကအလကအပတညလက အပပတငအ အပပခခပနထငပခငဆငပပငသပတသ နပလလသင
Bibliographic record
Abstract
Although it certainly comes with a unique set of challenges, the small number of projects carried out across Southeast Asia to date have demonstrated the efficacy that settlement archaeology holds for expanding on our traditional understandings of the region’s pre-industrial state formations. This discussion presents a brief historiography of the settlement archaeology projects that have focused on the “classical” states of Southeast Asia, and in doing so highlights the theories, methods, applications, and outcomes of these investigations. The need for more excavations to be carried out in the context of commoner habitation sites is underscored. အ ခြေ ေျ ခေ ထို င် ြေ င်း များ ခေ့ ော ော ရာ တွ င် စိ ေ် ခေါ် မှု များ စွာ ရှိ ခေ မ ည် ြြ စ် ခော် ေ ည်း၊ အခရှ့ခတာင် အာရှခေေတွင်ြြုေုြ်ေဲ့ကြေည့် ေုခတေေေုြ်ငေ်းအေည်းငယ်မှ ထွြ်ခြါ်ောခော နှစ်ေြ်တမ်း တွြ်ေျြ်မှုများေည် မမို့ြြမထွေ်းြားမီအခကြာင်းအ ရာများြို ြိုမိုေားေည်ေခောခြါြ်ောခစရေ် အတွြ် အခထာြ်အြူြြုေျြ်ရှိေည်။ ယေုခွွးခနွးတင်ြြမည့် အခြေေျခေထိုင်ြေင်းွိုင်ရာ ခရှးခောင်းေုခတေေခေ့ောမှုေ မိုင်းအြျဉ်းေျုြ်ေည် အခရှ့ခတာင်အာရှခေေရှိ ဂန္ထဝင်တွင်ခော မမို့ြြနိုင်ငံကြီးများြို အဓိြထားခေ့ောထားမြီး၊ ေီအိုရီများ၊ ေည်းေမ်းများ၊ ေြ်ခတွ့ခွာင်ရွြ် ေျြ်များနှင့် ထွြ်ခြါ်ောေည့် ရေေ်များြို တင်ြြမည်ြြစ်ြါေည်။ ခရှးခေတ်ောမာေ်အရြ်ေားများ ၏ အိမ်ယာအခြေေျခေထိုင်မှုများြို ခြာ်ထုတ်နိုင်ရေ်အတွြ် ထြ်မံေိုအြ်ခေမည့် တူးခြာ်ခေ့ောခရး ေုြ်ငေ်းများအခကြာင်းြို တင်ြြေွားမည်ြြစ်ြါေည်။
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".