In the fiscal year of 2023, 221 children who were adopted by American families were from India. In that same fiscal year, a further 200 children adopted by Americans were from Colombia, and 83 were from Bulgaria.

In the fiscal year of 2021, about 156 children from other countries were adopted by American families living in California, the highest of any U.S. state. Texas, Illinois, Virginia, and Florida rounded out the top five states for intercountry adoptions in that year.

Provides de-identified data on the number of applications, files and placements for adoptions in each year (separated by country).\r \r More information about this dataset can be found on the website of the Attorney-General's Department

In the fiscal year of 2022, about 51.81 percent of children adopted from abroad in the United States were female. In that fiscal year, there were 1,517 intercountry adoptions completed in the United States.

The Mission de l’adoption intercountry (MAI) is the central French authority for intercountry adoption, provided for in the 1993 Hague Convention on Protection of Children and Cooperation in Respect of Intercountry Adoption, to which France has been a party since 1998. Created by a decree of 14 April 2009, the MAI is placed within the Directorate of French Abroad and Consular Administration (DFAE), at the Ministry of Europe and Foreign Affairs. Since 2001, it has published each year a comprehensive report containing all the figures relating to the adoption of foreign children by French or foreign nationals residing in France. For the years after 1994, the collection of data is based on the extraction of statistics from the adoption file registration and monitoring software: — the census of long-stay adoption visas (VLSA) issued by French consular posts to children adopted abroad, on the advice of MAI, by French nationals or foreigners residing in France; — the information provided by authorised operators for adoptions carried out in countries of the European Union (Hungary, Bulgaria, etc.). For the years 1979-1993, the compilation of statistics by country of origin contains the data published in the 1995 Mattei report (Annex 8: status of visas granted to children adopted by French), corrected by some inconsistencies. Adoptions by French nationals whose habitual residence is abroad are not taken into account. Statistics on the various countries of origin and host countries have been compiled by Professor Peter Selman and are available on the website of the Hague Conference on Private International Law (www.hcch.net). The main features and developments of international adoption in France are published annually on the website of the Ministry of Europe and Foreign Affairs.

Financial overview and grant giving statistics of International Adoption Net

In 2022, 43 inter-country adoptions involving a child less than one year old were processed in the United States. Additionally, 593 children between the ages of five and 12 years old were adopted from abroad.

International adoptions processed through the citizenship grant program or through permanent residence.

In 2023, the total number of international adoption recorded in Spain was ***. According to the source, **** percent of the international adoptions were of children with * or less years of age.

Financial overview and grant giving statistics of America World Adoption Association

Regarding the number of international adoption requests issued by Spain in 2022, Vietnam ranked first with ** applications issued, followed by India with **. Hungary ranked fifth with ** applications.

Financial overview and grant giving statistics of Adoption Network-Domestic and International Inc.

This selection includes data related to SPC member countries and territories for some of the indicators available in the original database published by the World Bank.

Find more Pacific data on PDH.stat.

This graph presents the number of international adoptions carried out by parents in France in 2018, according to the continent of origin of the child. It displays that *** children adopted in France that year were from America.

IntroductionThis qualitative study explores the experiences of 12 Chinese women, aged 18–22, adopted by White families in the United States. While China’s one-child policy led to the international adoption of thousands of Chinese girls (1979–2015), qualitative research on their perspective about their adoption and cultural identity remains limited. Adoption is often misunderstood and stigmatized, particularly regarding its lasting impact. This study uses the intersectionality theoretical framework to understand the unique experiences of being Asian and adopted.Methods12 participants took part in 60- to 90-min semi-structured interviews conducted in person or via Zoom. 17 questions explored topics such as feelings about adoption, identity, and experiences with racism. Narrative and thematic content analysis were used to interpret the data.ResultsAll participants expressed gratitude for being adopted but many felt embarrassed and uncomfortable discussing adoption, especially in childhood. Their environments shaped how they navigated identity—those in less diverse areas felt especially alienated. Many identified more with White culture than Asian culture. Most felt a stronger connection to White culture than to their Asian heritage and faced challenges being fully accepted by either White or culturally Asian peer groups. Every participant recounted instances of racism or being subjected to stereotypes.DiscussionFindings emphasize the importance of awareness and support from families, peers, and professionals. Social workers should consider adoptees’ cultural identity and emotional experiences in assessments and therapy. Educating adoptive families and partners on racial and cultural dynamics can reduce isolation and strengthen support for transracial adoptees.

In 2021, a total of 48 children were adopted in Norway from outside the country. Of these, the highest number came from Colombia, followed by South Africa. Nine of the children came from countries not listed in the statistic. That year, the most common type of adoption in Norway was stepchildren being adopted.

In 2024, the number of South Korean children adopted abroad amounted to **, down from ** in the previous year. The number of adopted boys significantly exceeded that of girls. While international adoptions from South Korea have declined sharply over the past two decades, South Korean adoptees still made up the fifth-largest national group of U.S. overseas adoptions in 2018.

Financial overview and grant giving statistics of Rainbow Adoptions International Inc

Global AI Tool Adoption Across Industries and Regions (2023–2025)

A comprehensive, research-grade dataset capturing the adoption, usage, and impact of leading AI tools—such as ChatGPT, Midjourney, Stable Diffusion, Bard, and Claude—across multiple industries, countries, and user demographics. This dataset is designed for advanced analytics, machine learning, natural language processing, and business intelligence applications.

Dataset Overview

This dataset provides a panoramic view of how AI technologies are transforming business, industry, and society worldwide. Drawing inspiration from real-world adoption surveys, academic research, and industry reports, it enables users to:

• Analyze adoption rates of popular AI tools across regions and sectors.
• Study user demographics and company profiles influencing AI integration.
• Explore textual user feedback for sentiment and topic modeling.
• Perform time series analysis on AI adoption trends from 2023 to 2025.
• Benchmark industries, countries, and company sizes for AI readiness.

To add a column descriptor (column description) to your Kaggle dataset's Data Card, you should provide a clear and concise explanation for each column. This improves dataset usability and helps users understand your data structure, which is highly recommended for achieving a 10/10 usability score on Kaggle[2][9].

Below is a ready-to-copy Column Descriptions table for your dataset. You can paste this into the "Column Descriptions" section of your Kaggle Data Card (after clicking the pencil/edit icon in the Data tab)[2][9]:

Column Descriptions

Example Data

country,industry,ai_tool,adoption_rate,daily_active_users,year,user_feedback,age_group,company_size
USA,Technology,ChatGPT,78.5,5423,2024,"Great productivity boost for our team!",25-34,Enterprise
India,Healthcare,Midjourney,62.3,2345,2024,"Improved patient engagement and workflow.",35-44,SME
Germany,Manufacturing,Stable Diffusion,45.1,1842,2023,"Enhanced our design process.",45-54,Enterprise
Brazil,Retail,Bard,33.2,1200,2024,"Helped automate our customer support.",18-24,Startup
UK,Finance,Claude,55.7,2100,2023,"Increased accuracy in financial forecasting.",25-34,SME

How to Use This Dataset

1. Load and Preview the Data

import pandas as pd

df = pd.read_csv('/path/to/ai_adoption_dataset.csv')
print(df.head())
print(df.info())

2. Analyze Adoption Rates by Industry and Country

industry_adoption = df.groupby(['industry', 'country'])['adoption_rate'].mean().reset_index()
print(industry_adoption.sort_values(by='adoption_rate', ascending=False).head(10))

3. Visualize AI Tool Popularity

import matplotlib.pyplot as plt

tool_counts = df['ai_tool'].value_counts()
tool_counts.plot(kind='bar', title='AI Tool Usage Distribution')
plt.xlabel('AI Tool')
plt.ylabel('Number of Records')
plt.show()

4. Sentiment Analysis on User Feedback

from textblob import TextBlob

df['feedback_sentiment'] = df['user_feedback'].apply(lambda x: TextBlob(x).sentiment.polarity)
print(df[['user_feedback', 'feedback_sentiment']].head())

5. Time Series Analysis of Adoption Trends

yearly_trends = df.groupby(['year', 'ai_tool'])['adoption_rate'].mean().unstack()
yearly_trends.plot(marker='o', title='AI Tool Adoption Rate Over Time')
plt.xlabel('Year')
plt.ylabel('Average Adoption Rate (%)')
plt.show()

**6. Demographic Insights*...

The Adoption Regulation sets out the provisions of adoption under the Child, Youth and Family Enhancement Act. The regulation speaks to qualifications and procedures for licensing for adoption agencies, fees, home assessment reports, procedure for placements, and international adoptions.