cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.xh7q4h
title: Occurrence Download

description: A dataset containing 4852 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Peucedanum officinale L.",
 "HasCoordinate is true"
 ]
}

 The dataset includes 4852 records from 132 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052624-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b2dq7v
title: Occurrence Download

description: A dataset containing 838 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ampithoe lacertosa Spence Bate, 1858"
 ]
}

 The dataset includes 838 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0112666-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qqxnxa
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Uncia uncia (Schreber, 1775)"
 ]
}

 The dataset includes 6 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0092063-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9htwky
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cynoglossus dollfusi (Chabanaud, 1931)"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052643-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vtry7g
title: Occurrence Download

description: A dataset containing 513 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lepidium sagittulatum Thell."
 ]
}

 The dataset includes 513 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0151941-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t8vd3g
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Microdrillia fastosa (Hedley, 1907)"
 ]
}

 The dataset includes 32 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0092064-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jmps57
title: Occurrence Download

description: A dataset containing 71 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Nesogobius greeni Hoese & Larson, 2006"
 ]
}

 The dataset includes 71 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052645-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j49gcy
title: Occurrence Download

description: A dataset containing 48873 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lepidium virginicum L."
 ]
}

 The dataset includes 48873 records from 824 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0151831-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8uetap
title: Occurrence Download

description: A dataset containing 373677 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON((-104.46972 22.36768,-104.08896 22.80443,-104.07776 23.44275,-103.7978 23.8907,-103.83139 24.03629,-103.29385 24.42824,-102.48755 24.45064,-102.64433 25.03297,-102.8907 24.7418,-103.48423 25.25694,-103.28266 26.26483,-103.38344 26.61199,-104.27934 26.80236,-104.6041 26.35442,-104.86167 26.5224,-105.33202 26.4888,-105.99274 26.83596,-106.22791 26.58959,-106.51908 25.94006,-106.63107 25.5929,-106.98942 25.6489,-107.1686 25.50331,-107.2134 25.33533,-107.11261 25.04417,-106.91103 24.809,-106.51908 24.30505,-106.19432 24.37225,-105.92555 23.9019,-105.90315 23.62193,-105.58959 23.11799,-105.33202 23.0396,-105.04085 22.91642,-104.89527 22.64765,-104.46972 22.36768))"
 ]
}

 The dataset includes 373677 records from 572 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0162140-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18477752
title: NOBARQAROR IQTISODIY VAZIYATDA MOLIYAVIY RISKLARDAN HIMOYALANISH

description: Mazkur bo‘limda noaniqlik va risk tushunchalarining nazariy mazmuni, ularning iqtisodiy qarorlar qabul qilish jarayonidagi o‘rni va ahamiyati yoritilgan. Riskning obektiv va subektiv ehtimolliklar bilan bog‘liqligi, alternativ tanlov sharoitida namoyon bo‘lishi hamda noaniqlikni qisman bartaraf etish vositasi sifatidagi xususiyatlari tahlil qilingan. Shuningdek, riskning asosiy elementlari va muhim hislatlari - qarama-qarshilik, muqobillik va noaniqlik batafsil ochib berilgan. Moliyaviy risklarning mazmuni, ularning toza va spekulyativ turlari, kredit, foiz, valyuta hamda boy berilgan foyda risklari yoritilib, riskni boshqarish va kamaytirish usullari (diversifikatsiya, sug‘urtalash, limitlash va axborotdan foydalanish) ilmiy-nazariy jihatdan asoslab berilgan.
DOI: 10.5281/zenodo.18477751
title: NOBARQAROR IQTISODIY VAZIYATDA MOLIYAVIY RISKLARDAN HIMOYALANISH

description: Mazkur bo‘limda noaniqlik va risk tushunchalarining nazariy mazmuni, ularning iqtisodiy qarorlar qabul qilish jarayonidagi o‘rni va ahamiyati yoritilgan. Riskning obektiv va subektiv ehtimolliklar bilan bog‘liqligi, alternativ tanlov sharoitida namoyon bo‘lishi hamda noaniqlikni qisman bartaraf etish vositasi sifatidagi xususiyatlari tahlil qilingan. Shuningdek, riskning asosiy elementlari va muhim hislatlari - qarama-qarshilik, muqobillik va noaniqlik batafsil ochib berilgan. Moliyaviy risklarning mazmuni, ularning toza va spekulyativ turlari, kredit, foiz, valyuta hamda boy berilgan foyda risklari yoritilib, riskni boshqarish va kamaytirish usullari (diversifikatsiya, sug‘urtalash, limitlash va axborotdan foydalanish) ilmiy-nazariy jihatdan asoslab berilgan.
DOI: 10.5281/zenodo.15193078
title: Research Artifact – Cross-Project Flakiness: A Case Study of the OpenStack Ecosystem

description: This repository serves as the research artifact for the paper “Cross-Project Flakiness: A Case Study of the OpenStack Ecosystem”. It contains a dataset of flaky tests mined from OpenStack, along with their associated metadata, scripts for data collection, and the analysis logic to reproduce the findings in RQs 1–3.

Requirements & Warnings



Storage: This replication package is over 20 GB. Ensure you have sufficient disk space and a stable internet connection before downloading.

Hardware: Due to the size of the datasets, high-memory (RAM) is recommended for running the analysis notebook.

Database: A working installation of MongoDB and the mongorestore utility is required.


Replication Workflow

To replicate the results presented in the paper, follow these steps in order:



Extract Logs: Unzip zuul_job_logs_2024_mark_filtered.zip into the project root.

Restore Database: Use the mongorestore tool to import the study data from mongodb_archive.zip.

Run Analysis: Execute scripts/BuildingResults.ipynb. This notebook contains all the logic to process the data and replicate the results, figures, and tables presented in the paper.


Note: scripts/detect_flaky_tests.py is the script used for daily data collection. You do not need to run this for replication, as the output is already provided in the  output/ folders.

Repository Structure

scripts/ – Data Collection and Analysis



BuildingResults.ipynb: The main Jupyter notebook used to replicate key results.





Note: This script is resource-intensive and may take a significant amount of time to complete.



detect_flaky_tests.py: The script used to collect flaky tests on a daily basis.


data/ – Dataset Files



flaky_tests.json: All flaky tests identified in the study.

cleaned_flaky_tests.json: Flaky tests that appeared in more than one patch set.

flaky_builds_with_inline_comments.json: Flaky builds annotated with inline comments.

flaky_jobs_with_inline_comments.json: Flaky jobs annotated with inline comments.

inconsistent_flakiness_sample.xlsx: Manually labeled sample used for RQ3 analysis.


output/



Output files generated by the detect_flaky_tests.py script.


materials/



Visualizations and figures used in the paper.


survey/



Questionnaire design and developer responses.


External Data Archives (stored separately)



zuul_job_logs_2024_mark_filtered.zip: A collection of job logs gathered during the study.

mongodb_archive.zip: A MongoDB database dump containing data used in this study.


Replication on the Zuul Ecosystem



zuul_replication.zip: Scripts and data to replicate our results on the Zuul ecosystem.
DOI: 10.5281/zenodo.18476912
title: Research Artifact – Cross-Project Flakiness: A Case Study of the OpenStack Ecosystem

description: This repository serves as the research artifact for the paper “Cross-Project Flakiness: A Case Study of the OpenStack Ecosystem”. It contains a dataset of flaky tests mined from OpenStack, along with their associated metadata, scripts for data collection, and the analysis logic to reproduce the findings in RQs 1–3.

Requirements & Warnings



Storage: This replication package is over 20 GB. Ensure you have sufficient disk space and a stable internet connection before downloading.

Hardware: Due to the size of the datasets, high-memory (RAM) is recommended for running the analysis notebook.

Database: A working installation of MongoDB and the mongorestore utility is required.


Replication Workflow

To replicate the results presented in the paper, follow these steps in order:



Extract Logs: Unzip zuul_job_logs_2024_mark_filtered.zip into the project root.

Restore Database: Use the mongorestore tool to import the study data from mongodb_archive.zip.

Run Analysis: Execute scripts/BuildingResults.ipynb. This notebook contains all the logic to process the data and replicate the results, figures, and tables presented in the paper.


Note: scripts/detect_flaky_tests.py is the script used for daily data collection. You do not need to run this for replication, as the output is already provided in the  output/ folders.

Repository Structure

scripts/ – Data Collection and Analysis



BuildingResults.ipynb: The main Jupyter notebook used to replicate key results.





Note: This script is resource-intensive and may take a significant amount of time to complete.



detect_flaky_tests.py: The script used to collect flaky tests on a daily basis.


data/ – Dataset Files



flaky_tests.json: All flaky tests identified in the study.

cleaned_flaky_tests.json: Flaky tests that appeared in more than one patch set.

flaky_builds_with_inline_comments.json: Flaky builds annotated with inline comments.

flaky_jobs_with_inline_comments.json: Flaky jobs annotated with inline comments.

inconsistent_flakiness_sample.xlsx: Manually labeled sample used for RQ3 analysis.


output/



Output files generated by the detect_flaky_tests.py script.


materials/



Visualizations and figures used in the paper.


survey/



Questionnaire design and developer responses.


External Data Archives (stored separately)



zuul_job_logs_2024_mark_filtered.zip: A collection of job logs gathered during the study.

mongodb_archive.zip: A MongoDB database dump containing data used in this study.


Replication on the Zuul Ecosystem



zuul_replication.zip: Scripts and data to replicate our results on the Zuul ecosystem.
DOI: 10.15468/dl.6h8dhq
title: Occurrence Download

description: A dataset containing 242442 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((103.16283 18.99514,108.16283 18.99514,108.16283 23.99514,103.16283 23.99514,103.16283 18.99514))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Chordata"
 ]
}

 The dataset includes 242442 records from 195 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010894-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18476791
title: Syntactic complexity of machine and human translation

description: Syntactic complexity of machine and human translation
DOI: 10.5281/zenodo.18476790
title: Syntactic complexity of machine and human translation

description: Syntactic complexity of machine and human translation
DOI: 10.3535/42b-0v1-ml5
title: Xestia (Pachnobia) subgrisea (Staudinger, 1898)

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.15468/dl.mskzbz
title: Occurrence Download

description: A dataset containing 2104 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Paronychia argentea",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 2104 records from 101 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010913-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rskn6p
title: Occurrence Download

description: A dataset containing 941774 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((78.16283 23.99514,83.16283 23.99514,83.16283 28.99514,78.16283 28.99514,78.16283 23.99514))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Chordata"
 ]
}

 The dataset includes 941774 records from 95 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010893-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18477743
title: MАKTАBGАCHА YОSHDАGI BОLАLАRGА INGLIZ TILINI О'RGАTISHDА DIDАKTIK О'YINLАRNING АHАMIYАTI.

description: Ushbu mаqоlаdа bugungi kundа mаktаbgаchа tа’lim sоhаsidаgi rivоjlаnishlаr vа jаxоn tili hisоblаngаn ingliz tilining ertа yоshdаn о’rgаnishdаgi аfzаlliklаri hаqidа bаyоn qilingаn. Аynаn mаnа shu yо‘nаlishdа ilmiy tаdqiqоt ishlаri bаjаrilgаn. Bundаn tаshqаri  chet tilini о’rgаnishdа yоsh xususiyаtlаr,  shu  bilаn birgа  tilni о’rgаnish uchun zаrur bо’lgаn metоdlаrdаn о’yin metоdi vа undаn qаndаy fоydаlаnish hаqidаgi fikrlаr berib о’tilgаn.Mаzkur mаqоlаdа mаktаbgа tаyyоrlоv guruhlаridа qо’llаshimiz mumkun bо’lgаn bа’zi sаmаrаli о’yinlаr hаm yоritib berilgаn.
DOI: 10.5281/zenodo.18477771
title: BOSHLANG'ICH SINF O'QUVCHILARIDA AXLOQIY-ESTETIK TARBIYANI TAKOMILLASHTIRISHDA INTEGRATSIYALASHGAN TIZIMNI SHAKLLANTIRISH

description:  Ushbu maqolada boshlang‘ich sinf o‘quvchilarida axloqiy-estetik tarbiyani rivojlantirishda integratsiyalashgan ta’lim tizimining ahamiyati yoritilgan. Fanlararo integratsiya, ta’lim hamda tarbiya uyg‘unligi, faol pedagogik metodlardan foydalanish orqali o‘quvchilarda axloqiy qadriyatlar va estetik didni shakllantirish masalalari tahlil qilingan. Shuningdek, integratsiyalashgan tizimni amaliyotga tatbiq etish yo‘llari va kutilayotgan pedagogik natijalar asoslab berilgan.
DOI: 10.5281/zenodo.18477742
title: MАKTАBGАCHА YОSHDАGI BОLАLАRGА INGLIZ TILINI О'RGАTISHDА DIDАKTIK О'YINLАRNING АHАMIYАTI.

description: Ushbu mаqоlаdа bugungi kundа mаktаbgаchа tа’lim sоhаsidаgi rivоjlаnishlаr vа jаxоn tili hisоblаngаn ingliz tilining ertа yоshdаn о’rgаnishdаgi аfzаlliklаri hаqidа bаyоn qilingаn. Аynаn mаnа shu yо‘nаlishdа ilmiy tаdqiqоt ishlаri bаjаrilgаn. Bundаn tаshqаri  chet tilini о’rgаnishdа yоsh xususiyаtlаr,  shu  bilаn birgа  tilni о’rgаnish uchun zаrur bо’lgаn metоdlаrdаn о’yin metоdi vа undаn qаndаy fоydаlаnish hаqidаgi fikrlаr berib о’tilgаn.Mаzkur mаqоlаdа mаktаbgа tаyyоrlоv guruhlаridа qо’llаshimiz mumkun bо’lgаn bа’zi sаmаrаli о’yinlаr hаm yоritib berilgаn.
DOI: 10.5281/zenodo.18477770
title: BOSHLANG'ICH SINF O'QUVCHILARIDA AXLOQIY-ESTETIK TARBIYANI TAKOMILLASHTIRISHDA INTEGRATSIYALASHGAN TIZIMNI SHAKLLANTIRISH

description:  Ushbu maqolada boshlang‘ich sinf o‘quvchilarida axloqiy-estetik tarbiyani rivojlantirishda integratsiyalashgan ta’lim tizimining ahamiyati yoritilgan. Fanlararo integratsiya, ta’lim hamda tarbiya uyg‘unligi, faol pedagogik metodlardan foydalanish orqali o‘quvchilarda axloqiy qadriyatlar va estetik didni shakllantirish masalalari tahlil qilingan. Shuningdek, integratsiyalashgan tizimni amaliyotga tatbiq etish yo‘llari va kutilayotgan pedagogik natijalar asoslab berilgan.
DOI: 10.15468/dl.dbx5yu
title: Occurrence Download

description: A dataset containing 3741 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Korea, Republic of",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is one of (Falco peregrinus, Falco peregrinus babylonicus, Falco peregrinus japonensis, Falco peregrinus furuitii, Falco peregrinus macropus, Falco peregrinus ernesti, Falco peregrinus calidus, Falco peregrinus brookei, Falco peregrinus cassini, Falco peregrinus anatum)"
 ]
}

 The dataset includes 3741 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010914-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.31247239
title: Leveraging convolutional and graph networks for an unsupervised remote sensing labelling tool

description: Machine learning for remote sensing imaging relies on up-to-date and accurate labels for model training and testing. Labelling remote sensing imagery is time and cost intensive, requiring expert analysis. Previous labelling tools rely on pre-labelled data for training in order to label new unseen data. In this work, we define an unsupervised pipeline for finding and labelling geographical areas of similar context and content within Sentinel-2 satellite imagery. Our approach removes limitations of previous methods by utilizing segmentation with convolutional and graph neural networks to encode a more robust feature space for image comparison. Unlike previous approaches we segment the image into homogeneous regions of pixels that are grouped based on colour and spatial similarity. Graph neural networks are used to aggregate information about the surrounding segments enabling the feature representation to encode the local neighbourhood whilst preserving its own local information. This reduces outliers in the labelling tool, allows users to label at a granular level, and allows a rotationally invariant semantic relationship at the image level to be formed within the encoding space. Our pipeline achieves high contextual consistency, with similarity scores of SSIM = 0.96 and SAM = 0.21 under context-aware evaluation, demonstrating robust organization of the feature space for interactive labelling.
DOI: 10.6084/m9.figshare.31247239.v1
title: Leveraging convolutional and graph networks for an unsupervised remote sensing labelling tool

description: Machine learning for remote sensing imaging relies on up-to-date and accurate labels for model training and testing. Labelling remote sensing imagery is time and cost intensive, requiring expert analysis. Previous labelling tools rely on pre-labelled data for training in order to label new unseen data. In this work, we define an unsupervised pipeline for finding and labelling geographical areas of similar context and content within Sentinel-2 satellite imagery. Our approach removes limitations of previous methods by utilizing segmentation with convolutional and graph neural networks to encode a more robust feature space for image comparison. Unlike previous approaches we segment the image into homogeneous regions of pixels that are grouped based on colour and spatial similarity. Graph neural networks are used to aggregate information about the surrounding segments enabling the feature representation to encode the local neighbourhood whilst preserving its own local information. This reduces outliers in the labelling tool, allows users to label at a granular level, and allows a rotationally invariant semantic relationship at the image level to be formed within the encoding space. Our pipeline achieves high contextual consistency, with similarity scores of SSIM = 0.96 and SAM = 0.21 under context-aware evaluation, demonstrating robust organization of the feature space for interactive labelling.
DOI: 10.15468/dl.2v5fmj
title: Occurrence Download

description: A dataset containing 218 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Paronychia drummondii",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 218 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010915-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18477786
title: ZAMONAVIY TA'LIM JARAYONIDA O'QITUVCHINING EMPATIK SALOHIYATINI OSHIRISH MEXANIZMLARI

description: Ushbu ilmiy ishda zamonaviy ta’lim jarayonida o‘qituvchining empatik salohiyatini oshirish mexanizmlari nazariy va amaliy jihatdan tahlil etilgan. Tadqiqot davomida empatiyaning pedagogik faoliyatdagi o‘rni, uning o‘qituvchi va o‘quvchi o‘rtasidagi samarali muloqotni ta’minlashdagi ahamiyati yoritilgan. Empatik salohiyatni rivojlantirishning asosiy mexanizmlari sifatida kasbiy tayyorgarlik, refleksiya, emotsional intellekt, pedagogik treninglar, inklyuziv ta’lim muhiti hamda pedagogik hamkorlik masalalari ilmiy manbalar asosida asoslab berilgan. Tadqiqot natijalari empatiyaga asoslangan pedagogik yondashuv ta’lim sifatini oshirish va insonparvar ta’lim muhitini shakllantirishga xizmat qilishini ko‘rsatadi.
DOI: 10.5281/zenodo.18477787
title: ZAMONAVIY TA'LIM JARAYONIDA O'QITUVCHINING EMPATIK SALOHIYATINI OSHIRISH MEXANIZMLARI

description: Ushbu ilmiy ishda zamonaviy ta’lim jarayonida o‘qituvchining empatik salohiyatini oshirish mexanizmlari nazariy va amaliy jihatdan tahlil etilgan. Tadqiqot davomida empatiyaning pedagogik faoliyatdagi o‘rni, uning o‘qituvchi va o‘quvchi o‘rtasidagi samarali muloqotni ta’minlashdagi ahamiyati yoritilgan. Empatik salohiyatni rivojlantirishning asosiy mexanizmlari sifatida kasbiy tayyorgarlik, refleksiya, emotsional intellekt, pedagogik treninglar, inklyuziv ta’lim muhiti hamda pedagogik hamkorlik masalalari ilmiy manbalar asosida asoslab berilgan. Tadqiqot natijalari empatiyaga asoslangan pedagogik yondashuv ta’lim sifatini oshirish va insonparvar ta’lim muhitini shakllantirishga xizmat qilishini ko‘rsatadi.
DOI: 10.5281/zenodo.17462463
title: Dataset and Instruments for The Influence of Magdalene.co Instagram Content on Gen Z Attitude Toward Feminism and Women's Empowerment in Jakarta (IMCOM 2026, Paper ID 154)
DOI: 10.5281/zenodo.17462462
title: Dataset and Instruments for The Influence of Magdalene.co Instagram Content on Gen Z Attitude Toward Feminism and Women's Empowerment in Jakarta (IMCOM 2026, Paper ID 154)