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Record W4405911830 · doi:10.29173/anlk817

From Early Migrations to Colonial Encounters: Archaeological Research on the Mannar-Jaffna Seaboard, Sri Lanka

2024· article· en· W4405911830 on OpenAlexfundno aff
Thilanka Siriwardana

Bibliographic record

VenueAncient Lanka · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Maritime and Colonial Histories
Canadian institutionsnot available
FundersRijksuniversiteit GroningenRoyal Asiatic Society of Great Britain and IrelandMount Royal UniversityUniversity of PennsylvaniaUniversity of OxfordHarvard UniversityNational Geographic Society
KeywordsSri lankaColonialismGeographyArchaeologyAncient historyHistorySouth asia

Abstract

fetched live from OpenAlex

The Mannar-Jaffna Seaboard (MJS), a region that played a critical role in Sri Lanka's past, has seen over 150 years of archaeological research. While recent research programs employing advanced scientific techniques have been implemented, significant knowledge gaps persist. A comprehensive approach is needed to synthesize the archaeological past from prehistoric times to the recent colonial period. This review highlights some research questions emerging from previous studies advocating for further exploration. Since the MJS possesses an intertwined history with its coastal settings and resources, this article’s main focus is on understudied sites and periods to enhance the knowledge on coastal archaeological studies of Sri Lanka. Revisiting overlooked publications and addressing challenges such as data management and research integrity are crucial to gaining a more complete understanding of this region's complex past. This comprehensive compilation encompasses all known works on the MJS, serving as an essential resource for future researchers to build upon.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0040.004
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.074
GPT teacher head0.378
Teacher spread0.305 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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