Question 1

What are the key details for the project “Machine learning in the Measurement of Gender Bias in the Demand for Employment”?

Accepted Answer

The project “Machine learning in the Measurement of Gender Bias in the Demand for Employment” is an infrastructure initiative in the Government sector, located in Regional. Taiyo aggregates data on it from Inter-American Development Bank (IADB).

Question 2

What is the latest status of the project “Machine learning in the Measurement of Gender Bias in the Demand for Employment”?

Accepted Answer

The status recorded for “Machine learning in the Measurement of Gender Bias in the Demand for Employment” is closed.

Question 3

Who are the main government, EPC, and private stakeholders for “Machine learning in the Measurement of Gender Bias in the Demand for Employment”?

Accepted Answer

Taiyo maps the stakeholders of “Machine learning in the Measurement of Gender Bias in the Demand for Employment”: government bodies (Inter-American Development Bank (IDB)).

Question 4

What is the budget and commercial profile for the project “Machine learning in the Measurement of Gender Bias in the Demand for Employment”?

Accepted Answer

Taiyo normalizes the budget of “Machine learning in the Measurement of Gender Bias in the Demand for Employment” to USD 200000.

Question 5

Where can I verify the source and access all details for “Machine learning in the Measurement of Gender Bias in the Demand for Employment”?

Accepted Answer

This Taiyo project page references Inter-American Development Bank (IADB) along with the original URL (https://www.iadb.org/en/project/RG-T3157). Taiyo standardizes official data into a consistent, searchable project profile.

Sponsoring Agency	Obfuscated Data
Company	Obfuscated Data

Original status	closed
Taiyo status	Obfuscated Data
Taiyo last update	00-00-0000
Available timestamps	00-00-0000
Available timestamp type	Obfuscated Data

Contact name	Obfuscated Data
Phone	0000000000
Email	ObfuscatedData@email.com
Address	Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data

Description	The aim of this TC is to provide rigorous evidence on the dimension of explicit and implicit gender discrimination in employment notices and their impact on the likelihood of a woman applying to a job.
Original sub-sector	Obfuscated
Original Currency	USD
Original budget	000000000000000
Procurement method	Obfuscated Data
Budget	000000000000000

Region	Obfuscated
Country	Obfuscated
State	Obfuscated Data
County	Obfuscated
Location	Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data

Source reliability	High
Data quality score	100%
Source	Obfuscated Data
URL	obfuscated_data,obfuscateddata.com

Project Type	Obfuscated Data
Article Published Date	Obfuscated Data

Machine learning in the Measurement of Gender Bias in the Demand for Employment

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