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Record W4413854047 · doi:10.1177/24559296251363112

Towards Safeguarding the <i>Dap-ay</i> , <i>Patpatayan</i> and <i>Babawi-an</i> as an Indigenous Ceremonial Landscape of the Northern Kankanaey in Central Sagada, Mountain Province, Philippines

2025· article· en· W4413854047 on OpenAlexaff
Jan Haenraets, Alixa Lacerna, B Sison-Gilmore

Bibliographic record

VenueJournal of Heritage Management · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPhilippine History and Culture
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSafeguardingIndigenousGeographyArchaeologyEnvironmental protectionEnvironmental resource managementEcologyEnvironmental science

Abstract

fetched live from OpenAlex

Sagada is a municipality in the Philippine Cordillera Central mountain range in the northwest of Luzon Island. Throughout much of its history, Sagada’s Northern Kankanaey indigenous community practised subsistence farming. Today, living traditions in Sagada remain closely interwoven with indigenous knowledge and engagement with the land, traditional practices and rituals, conservation of indigenous places and cooperative community approaches. The rituals associated with the begnas —a collection of agro-cultural ceremonies and a community feast—are still practised but face the risk of discontinuation or being performed with compromised integrity. The article presents three types of indigenous sacred places integral to the begnas . These places comprise a landscape of ceremonies, rituals and customs of Sagada Kankanaey life and identity. The dap-ay is a stone-paved council meeting area within villages, the patpatayan is a sacred tree or grove on a hilltop and the babawi-an is used for omen observation during rituals. The study illuminates their role in the begnas and the broader cultural landscape, as well as varying approaches to conserving these sites. Safeguarding these tangible places is essential to safeguarding the intangible cultural practices and indigenous knowledge, ultimately ensuring the well-being of the Kankanaey community.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.612
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.254
Teacher spread0.247 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2025
Admission routes1
Has abstractyes

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