Before Bagan: Using Archaeological Data Sets to Assess the Traditional Historical Narrative | ပဂမတငမကလ၏အစဉအလသမငအဆအမနမက ရရငသရတသ နပညပဆငအခကအလကမအသပပ၍ဆနစစပခင
Bibliographic record
Abstract
What we know about Bagan derives almost exclusively from historical sources – namely retrospective chronicles, inscriptions, and changing architectural styles. To date, archaeological excavations have played a limited role in augmenting or challenging this traditional narrative. This is unfortunate, because small scale excavations within Bagan’s peri-urban settlement zone, and within the walled and moated “royal city,” have demonstrated considerable knowledge about the city’s past. This is especially true for the Pre-Bagan phase (600-1044 CE). This presentation documents what we think we know about the time “before Bagan,” using the established sources, and assesses this narrative using information from contemporaneous excavation levels. ပုဂံခေတ်ယဉ်ချေးမှုအခြျာင်းျို သမိုင်းအေေျ်လျ်မေားဖြစ်သည့် အစဉ်အလာရာဇဝင်မှတ်တမ်းမေား၊ ချောျ်စာမေား၊ နှင့် ခဖပာင်းလဲလာေဲ့သည့်ဗိသုျာပုံ စံမေားမှသာလေင် သိြျရသည်။ နှစ်သျ်တမ်း သတ်မှတ်ရန်အတွျ် ခရှးခောင်းသုခတ သနဆိုင်ရာတူးခြာ်ခလ့လာမှုမေားသည်အစဉ်အလာအဆိုအမိန့် မေားျို ခဝြန်စစ်ခဆးရန် (သို့) ဖပင်ဆင်ြျရန် လုံခလာျ်မှုမရှိြျခသးခေေ။ ပုဂံမမို့ရိုး၊ ျေုံးဧရိယာနှင့် မမို့အစွန်အြေ ားခနရာမေားတွင်ခလ့လာေဲ့သည့် အနည်းငယ်မျှခသာ စမ်းသပ်တူးခြာ်ခလ့လာမှုမေားျ ပုဂံမမို့၏အတိတ်ျာလျို သိရှိနိုင်ခစရန် ရုပ်လုံးခြာ်ြပခနြျသည်။ ပုဂံမမို့ဖပမတိုင်မီျာလ (၆၀၀-၁၀၄၄ စီအီး)နှစ်သျ်တမ်းတွျ်ေေျ်မှုအခဖြမေားရရှိေဲ့သည်။ ယေုတင်ဖပမည့် စာတမ်းမှာ ပုဂံခေတ် မတိုင်မီျာလအခြျာင်းအရာမေားျို ခရှးခောင်းသုခတသနပ ညာရပ်ဆိုင်ရာတူးခြာ်မှုရလဒ်မေားနှင့် အစဉ်အလာအဆိုအမိန့်အေေျ်အလျ်မေားျို စစ်ခဆးအသုံးဖပုလေျ် မည်ျဲ့သို့ခတွးခတာသိရှိလာနိုင် ခြျာင်းျို တင်ဖပမည်ဖြစ်ပါသည်။
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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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".