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Record W7125896647 · doi:10.52046/jssh.v5i2.2662

Resource Constraints and the Role of Executive Disposition Strategies in Women's Empowerment Policies in Ternate City

2025· article· W7125896647 on OpenAlexaff
Musdalifah Musdalifah

Bibliographic record

VenueJURNAL SAINS SOSIAL DAN HUMANIORA (JSSH) · 2025
Typearticle
Language
FieldSocial Sciences
TopicPublic Administration in Developing Nations
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsDispositionEmpowermentGovernment (linguistics)Human resourcesBridging (networking)Local governmentResource (disambiguation)Public policy

Abstract

fetched live from OpenAlex

The women’s empowerment program through home-based industries in Ternate City is a strategic initiative by the local government to promote economic independence and gender equality. However, its implementation faces various challenges, especially the limited availability of resources such as budget, personnel, and supporting facilities. This study aims to analyze the role of implementers’ disposition, namely attitudes, commitment, and coordination capacity in ensuring the effectiveness of policy implementation under such constraints. Using a descriptive qualitative approach, data were collected through interviews and documentation, and analyzed thematically. The findings show that implementers’ disposition is a critical factor in policy success. Strong commitment and cross-sector coordination have enabled the program to continue operating adaptively and responsively, despite structural limitations. This study emphasizes that human factors particularly the disposition of implementers play a strategic role in bridging formal policy with field realities.

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)0.004
metaresearch head score (Gemma)0.005
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 score0.033
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.004
Scholarly communication0.0040.001
Open science0.0010.004
Research integrity0.0010.001
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 head0.011
GPT teacher head0.308
Teacher spread0.297 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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