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Record W3199229429 · doi:10.32870/eees.v28i82.7163

La mujer: pieza clave en el desarrollo. Estrategias contenidas en la agenda 2030

2021· article· es· W3199229429 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEspiral estudios sobre Estado y sociedad · 2021
Typearticle
Languagees
FieldSocial Sciences
TopicSocial Issues and Sustainability
Canadian institutionsCentre de Santé et de Services Sociaux Cavendish
Fundersnot available
KeywordsSustainable developmentPerspective (graphical)PoliticsWork (physics)Face (sociological concept)SociologyPolitical scienceEconomic growthSocial scienceEconomicsComputer science

Abstract

fetched live from OpenAlex

The participation of women in the different economic, political, social and environmental sectors constitutes the key piece to achieve that sustainable human development that we so long for. Its strength, intelligence, ability to manage resources, as well as its ability to care for others and the environment that surrounds it make it the engine of sustainable human development. However, one of the obstacles that millions of women around the world have to face is the poor recognition of their rights in all areas, making them susceptible to situations of discrimination, violence and social exclusion. Although great progress has been made in the last 40 years in incorporating the gender perspective in international agendas, there are still important challenges regarding their equal and full participation in international society. For this reason, we carried out an analysis on the incorporation of a gender perspective in the 17 Sustainable Development Goals (SDGs), highlighting the importance of women's participation in each of the SDGs. Therefore, this work aims to analyze the incorporation of the gender perspective in the 17 Sustainable Development Goals (SDGs), highlighting the importance of women's participation in each of the SDGs and determining the challenges that arise in the implementation of the SDGs from a gender perspective. Being the descriptive methodology, based on the analysis of qualitative and quantitative data, the one used to carry out this work.

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.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.528
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.002
Science and technology studies0.0020.003
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
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 head0.024
GPT teacher head0.351
Teacher spread0.327 · 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