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Report on Human Rights Internet
Unless we choose to continue to develop this data, I think it is about as clean as it
is going to get. I have attached 11 graphs to this document for your perusal. I will
discuss them again briefly at the meeting.
I will first describe the content of the graphs and then discuss some of the issues
that remain regarding this dataset.
Graphs
1. Births: Births of Human Rights NGOs and INGOs. Similar to what was presented a
few weeks ago but with better and more reliable data
2. IGOs: This is the data Emilie compiled presented without “missing” years. Keiko
suggested that this would highlight the peaks and valleys.
3. Wotipka: INGO/NGO data based on Wotipka classification of organizations. This
was presented earlier, but the dataset is much cleaner now
4. Suarez: INGO/NGO data based on Suarez classification of organizations. This was
also presented earlier, but the dataset is cleaner.
5. INGO: A comparison of Suarez and Wotipka for INGOs. It is interesting to note that
the distribution is similar for both lines. My coding yields far more INGOs, but
this does not change how they are distributed by year.
6. NGO: A comparison of Suarez and Wotipka for NGOs. These charts are very similar.
If there were not so much missing data the Wotipka graph would have FAR more
NGOs, but based on founding dates the graphs look quite similar.
7. NGOs and Regions: This graph looks at the regional distribution of INGOs/NGOs
based on founding date. Regions are based on Polity IV. I left censor at 1900
because there are so few organizations before that time.
8. NGOs and Regions2: This graph also looks at the regional distribution of
INGOs/NGOs based on founding date. Regions are based on a classification
scheme I developed when creating XNXT2000. I used the CIA factbook and a
World Bank map of the world to designate regions. I think it is more reasonable
and useful than the Polity IV measure. If we work on a paper using this region
variable it would be fairly easy to create an appendix listing the countries in each
region.
9. West and the Rest, Pt. 1: This is a graph that is easier to see than the previous graph
because it includes less regions. It is based on the CIA Regions and compares 3
regions to the West.
10. West and the Rest, Pt.2: This is a continuation of the previous graph, comparing the
remaining 3 regions to the West. Graphs 9 and 10 are EXACTLY the same as
graph 8 when combined.
11. Human Rights Education Organizations: This graph is part of a different project that
I am working on for my dissertation and a paper with Chiqui. It is a first attempt
to code all human rights education organizations in the world. I discuss this more
below.
Missing Data
This dataset still has considerable missing data. There are 3,343 organizations
with data for founding data. There are 3,302 organizations with no data for founding
date. I still view this as a problem but perhaps nobody else does. I’m not so sure that we
need to go hunting for more variables regarding the expansion of the human rights regime
right now, but it might be worth it to spend some time investigating the internet for
founding dates.
Remaining Data to be Coded
Keiko and Emilie
Keiko and Emilie are working on measures for “Declarations and Conventions”
and “Human Rights Conferences.” I have left this to them and they will present on this
issue at a later date. I made an initial coding effort with this, but it was very preliminary.
The idea is to add these measures to the measures from the Human Rights Internet in
order to create a paper like the Meyer et al. paper on the environment for International
Organization.
David
I have been working to code organizations with an interest in human rights
education, and I guess this is as good an opportunity as any to discuss initial findings.
This information will be most useful for a paper I hope to work on with Chiqui, but it is
definitely related to the other coding several of us have been involved with.
The Human Rights Internet lists 370 organizations dedicated to education. I
compiled this list by looking at a variety of variables in the dataset. From this group of
370 I determined that 80 of them could be identified as organizations that directly work
on human rights education.
I also coded the Human Rights Education Associates Resourcebook for Human
Rights Education. From that source I was able to code 218 organizations.
Finally, I coded the website for UNESCO Chairs in Human Rights Education.
There are several types of UNESCO Chairs but I coded only those with a specific
mention of human rights.
I put all three of these sources together to create a new dataset with 318
organizations or bodies in the world that focus on human rights education. Because the
main source I used to code these organizations did not include founding dates I have only
been able to identify 145 founding years. Hopefully I will be able to improve this with
internet searches and emails during the next few weeks.
As a next step, a very useful set of books to code would be the UNESCO
directory of human rights training centers. Many of these organizations might already be
included in what I have done, but UNESCO has published three of these books, and
perhaps now a fourth. These training centers are intended for adults, meaning that they
are university level courses or practitioner training agencies. UNESCO did not try to
capture the organizations working on HRE at the primary and secondary level.
Coding Protocols
For those of you who might not have seen it I am going to include the codebook
that Emilie sent out the other day regarding IGOs. I will then describe the coding
protocol for the dataset I have been working with. I will then discuss specific variables in
this dataset
Human Rights IGO Codebook: Emilie Hafner-Burton
The human rights intergovernmental organization (IGO) dataset was coded by Emilie
Hafner-Burton, June 2003.
This dataset contains 109 IGOs and 10 variables.
Coding Source
The organizations were selected from the complete population of Union of International
Associations (UIA) organizations, available on cd-rom (1999/2000). Please note that this
population of IGOs is not the same in the UIA book format or the UIA website, although
there is great overlap in organizations.
Sample Method
Organizations were chosen if they were UIA classified by the terms “rights” or “right.”
Only those organizations that are explicitly described using these terms are included in
the sample.
To determine whether an organization is a “rights” organization from the cd-rom, I
queried “human,” “right,” and “rights” on the query form in the database.
I read the profile of all 740(+) organizations identified by the query. I selected those
organizations that the UIA identifies as IGOs.
Sample Exclusions
Certain categories of organizations were excluded from the sample. Treaties and
unconfirmed bodies are excluded from the IGO data. Those IGOs that are proposed but
not yet in existence are excluded from the sample. Temporary missions are excluded
from the sample. IGO trust funds and voluntary funds are excluded from the sample.
Specific organizations were excluded from the sample. The United Nations Postal
Administration (UNPA) is excluded from the sample, even though the UIA does identify
human “rights.” The UNPA issued stamps on the theme of human rights and is not a
human rights organization. UNESCO Associated Schools Project for Promoting
Education for Peace, Human Rights, Democracy and International Understanding (ASP)
was excluded from the sample. Although the UIA identifies this organization as an IGO,
membership consists of 4,613 participating institutions. States are not members. Países
Africanos de Lingua Oficial Portuguesa (PALOP) is excluded from the sample because it
has no permanent secretariat.
I coded several variables from the UIA sample of human rights IGOs.
IGO Variables
(1) IGO name: This variable codes the organization name as it appears in the UIA.
(2) Founding Date: This variable codes the organization founding date as it appears in the
UIA. 3 founding dates are reported missing.
(3) Major Aim: This is a binary variable {01}. I code 1 if the language of “rights”
pertaining to any human (and not animal) group appeared in the UIA field
organizational aim. I code 0 if the language of “rights” pertaining to any human (and
not animal) group did not appear in the UIA field organizational aim.
(4) Documents and Bodies: This is a binary variable {01}. I code 1 if the UIA reports
that the organization has established human rights documents (protocols, treaties,
etc.) or human rights bodies (commissions, sub-committees, working groups, etc.). I
code 0 if the UIA does not report that the organization has established human rights
documents (protocols, treaties, etc.) or human rights bodies (commissions, sub-
committees, working groups, etc.).
(5) NGO Relations: This is a binary variable {01}. I code 1 if the UIA identifies
affiliation with any human rights nongovernmental organization (NGO). I code 0 if
the UIA does not identify affiliation with any human rights NGO.
(6) Other Activities: This is a binary variable {01}. I code 1 if the language of “rights”
pertaining to any human (and not animal) group appeared in the UIA field
organizational activities. I code 0 if the language of “rights” pertaining to any human
(and not animal) group did not appear in the UIA field organizational activities.
(7) Region: This variable indicates the region of IGO membership. It is classified by the
following categories: Africa; Americas; Asia and Pacific; Europe; Middle East;
World.
(8) Parent Organization. This variable indicates whether the IGO is a subsidiary body of
another organization, such as the United Nations (UN).
(9) Parent Organization 2. This variable indicates whether the IGO is a subsidiary body
of another parent organization, such as the United Nations Development Programme
(UNDP).
(10) Rating: This code is consistent with previous codes on health organizations and
human rights organizations. I code 3 if the language of “rights” appears in an
organization’s aims or activities (and it refers to human rights or aims or “rights” is
included in the organization name). I code 2 if “rights” are included in categories
other than aims or activities (such as documents and bodies or NGOs).
Human Rights Internet and UIA Database
This dataset is based on an original coding of the Human Rights Internet database
in 2000 by Kiyoteru Tsutsui. This coding included the entire population of organizations
in the database at the time. After cleaning up the data and eliminating repeats there are
6,151 organizations from that dataset. In addition to this dataset, 495 original
organizations came from a dataset coded by Kiyoteru Tsutsui and Christine Min
Wotipka. They coded these organizations in the following manner (This information is
taken directly from a document they sent me):
“CODING SCHEME: The main source of data in the analyses is the Yearbook of
International Organizations published annually by the Union of International
Associations. The coding was done using mainly the categorization employed in the
Yearbook. The Yearbook has various headings under which it lists organization names,
and users can find more information on each organization in the organization descriptions
section, which is referenced in the organization list. Since the categorization changes over
time toward more categories and specifications, identifying organizations that qualify as a
HRINGO is the easiest for 1998 Yearbook and requires the most effort for 1978.
In the 1998 Yearbook, there is a category “human rights organizations”, from
which most of relevant organizations are coded. Although this expedites the coding
process tremendously, there are some organizations that qualify as HRINGOs by my
definition but do not appear in this category. Thus, organizations listed under other
headings such as “innovative change/rights” and “mankind/rights” are examined, and
qualified organizations are incorporated in the data set.
For 1988 data, I had to expand the scope and code organizations in many more
categories. The categories used include “rights”, “justice”, “equality”, “discrimination”,
and “humanity”. Many organizations are listed in multiple categories, but examining
these categories produced a more comprehensive list of possible HRINGOs.
In 1978, the Yearbook’s categorization was more primitive, and coding of
HRINGOs required the most work. It used two types of subject headings: English
subject, which uses organization names as the key, and classified subject, which uses
organization aims and activities as the key. I first coded organizations under English
subject headings “human” and “rights”. Then, I coded organizations under classified
subject headings “social welfare”, “women”, “trade union”, and “religion, ethics,
morals”. Most organizations listed in the last three headings are included in the heading
“social welfare” but examination of these headings did result in several more
organizations in the data set.
The initial coding was done in an inclusive manner, including organizations that
may not qualify as HRINGOs in more careful examination. Thus, after coding all these
organizations, the data files still had some organizations that are not HRINGOs according
to my definition, particularly for 1978 and 1988 files. To sort out HRINGOs from these
bigger data, I ranked each organization using a four-point scheme (0 to 3). Each score
means the following.
3 – definitely a HRINGO
2 – activities relevant to global human rights but does not qualify as a HRINGO
1 – activities remotely relevant to global human rights and not a HRINGO
0 – not a HRINGO
Those organizations that rank as “3” work primarily for promotion of human
rights as internationally recognized, and their work is not intended exclusively for their
constituents.
Those with the score of “2” are organizations that might contribute to promotion
and protection of global human rights, but do not work explicitly for that or do not work
for long term social changes. Humanitarian organizations that aid refugees and natural
disaster victims fall in this category to the extent that they aid any victims regardless of
political or religious backgrounds and do not focus on changing social systems that
produce these victims. Ethnic and religious organizations that do not work for justice,
equality or rights, women’s organizations that are focused exclusively on research
activities, authors’ rights organizations that deal with commercial/intellectual rights but
not with freedom of expression are in this category as well.
Organizations that have a score of “1” are mostly development organizations and
trade unions that only work for their members. Development organizations that do not
work for fundamental human rights do not qualify as HRINGOs. They typically have as
their goals “improvement in the quality of life” or “upgrading the standard of living”.
Trade unions and other professional organizations, such as organizations for professional
women, are also in this category to the extent they work exclusively for the interests of
their constituents.
The last category has a few organizations that promote different kinds of “rights”
than human rights. Animal rights organizations provide a typical example. Pedestrian
rights groups or mechanical reproduction rights organizations are also picked up because
of “rights” in their names. These organizations present few problems, as they are clearly
not HRINGOs.
In the following analyses, I used only the organizations that have the score of 3.
This means that the data include only organizations that work explicitly to promote and
protect internationally recognized human rights in the long term. The data files include
107 (1978), 200 (1988), and 553 (1998) organizations, indicating a dramatic increase in
HRINGO activities over the last thirty years. I explore this explosion of HRINGOs
further in the following sections.”
So, this dataset I am working with includes the population of organizations from
the Human Rights Internet and the human rights INGOs coded as mentioned above. So
far this is a complete accounting of how the datasets we are working with have been
compiled.
The only bit of information worth adding is that when there was a repeat I deleted
it from the larger dataset – the Human Rights Internet database – and created a new
variable to indicate that the organization appeared in both datasets.
HRI_UIA Variables
The following is a summary of some of the most relevant variables in what I will
be calling the HRI_UIA dataset.
1. listcode: This variable is a proxy for the organization name which is often much to
large to include in the dataset. If for whatever reason we actually need to know the
organization name the listcode variable aligns with the finished Excel Spreadsheet.
2. newid3: The traditional merge code variable in case we plan to add nation-level data
3. region:
1 North/South America
2 Europe
3 Africa
4 Middle East
5 Asia
6 Oceania
4. regiona
1 Sub-Saharan Africa
2 East Asia
3 East Europe
4 Latin America
5 Middle East and North Africa
6 South Asia
7 West
5. country: Country where the organization is located.
6. alsohri: Organization that was in HRI and UIA dataset
7. coder: Source of the data on the organization
8. name: Organization name – To be deleted from dataset for statistical analysis
9. edgoal: Does the organization have an org focus? 1 = Yes
10. hre: Does the organization have a focus on HRE? 1 = Yes
11. orgchaps: Is the organization a chapter or a parent for another organization? 1 = Yes
12. founded: Founding date for the organization
13. geofocus: Geographic focus of the organization (not clean)
14. newissue: Issue focus of the organization (specific codes at the end)
15. wotingo: Wotipka INGO measure based on UIA definitions. This definition is
based on membership from more than one country. Dichotomous.
16. wotngo: Wotipka NGO measure based on UIA definition as above. Dichotomous.
17. suaringo: Suarez INGO measure based on HRI definitions. Broader conception of
INGO than the UIA measure. Since there is no membership data for HRI this
measure is loosely based on the idea that organizations with an international focus
or working in various countries are INGOs, regardless of membership.
Dichotomous.
18. suarngo: Suarez NGO measure based on HRI definition as above. Dichotomous.
19. opssuar2: Suarez INGO/NGO measure. This is a polytomous variable with the
following classifications
F = Foundation
I = INGOs
L = Local
N = National
R = Regional
20. typeorg: Type of organization (specific codes at the end)
Codes for variable 14: Organization Issue Focus (Primary Focus)
1 = Civil/Political Rights (444)
2 = Health (148)
3 = Children (256)
4 = Democracy (163)
5 = Development (286)
6 = Education (230)
7 = Environment (71)
8 = Foreign Policy (56)
9 = Indigenous Peoples (316)
10 = Women (719)
11 = Refugees (212)
13 = Community Dev’t (48)
14 = Cultural Rights (51)
15 = Death Penalty (23)
16 = Disabled (42)
17 = Economic/Social Rights (69)
18 = Monitoring/Humanitarian Aid (88)
20 = Housing (32)
21 = Justice & Peace (159)
22 = Labor (178)
23 = Land (33)
24 = Minorities (117)
25 = Political Prisoners (81)
26 = Law/Rule of Law (294)
27 = Self-Determination (88)
28 = Torture/Genocide (175)
29 = United Nations (40)
30 = Conflict Resolution (33)
31 = Other (209)
32 = General Human Rights (1684)
33 = Peace & Reconciliation (145)
34 = Racism (65)
36 = Sexual Orientation (12)
37 = Youth/Students (44)
Codes for variable 20: Organization Type
1 = Academic or University Based (215)
2 = Bar Association (16)
3 = Children’s Organization (126)
4 = Coalition, Consortium (222)
5 = Community or Neighborhood Organization (6)
6 = Development Organization (87)
7 = Disabled Persons’ Organization (13)
8 = Documentation Center (191)
9 = Education Organization (105)
10 = Environmental Org (23)
11 = Ethnically-Based Org (120)
12 = Families of Victims (32)
13 = Federation (59)
14 = Funding Agency (52)
15 = Gay and Lesbian (5)
16 = Health (108)
17 = HR Ogr (901)
18 = Humanitarian or Refugee (104)
19 = Indigenous (206)
20 = Journalist, Writer, Publisher (72)
21 = Legally-Oriented (393)
22 = Library or Archives (9)
23 = Lobby Group (19)
24 = Media (42)
25 = Museum (5)
26 = Parliamentary (18)
27 = Peace Organization (49)
28 = Political Group/ Org (25)
29 = Professional Association (37)
30 = Publication (42)
31 = Religious Org (536)
32 = Research (296)
33 = Science (5)
34 = Service (42)
35 = Social Service (25)
36 = Solidarity Group (227)
37 = Students Organization (34)
38 = Trade Union (77)
39 = Tribunal (9)
40 = United Nations Body or Program (20)
41 = Women’s Org (467)
42 = Youth Organization (31)
999 = Other (63)
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Births
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IGO Data
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WotINGO
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Wotipka INGO/NGO Data
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WotNGO
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SuarINGO
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Suarez INGO/NGO Data
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SuarNGO
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WotINGO
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INGO Data
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SuarINGO
39
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WotNGO
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NGO Data
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SuarNGO
39
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36
Americas
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39
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42
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45
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Europe
48
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51
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54
19
Africa
57
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60
NGOs and Regions: Polity IV
19
63
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Mideast
66
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69
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72
Asia
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75
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81
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Sub-Sah Africa
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East Asia
33
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36
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39
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42
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East Europe
45
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48
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54
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Latin America
60
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63
NGO Regions: CIA and World Bank
19
66
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69
Middle East 19
72
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78
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South Asia
84
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Western
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Western
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Southeast Asia
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The West and the Rest, Part 1
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Middle East
66
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Latin America
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Eastern Europe
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East Asia
60
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The West and the Rest, Part 2
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SubSah Africa
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