Metagora Training Materials

Encyclopedia of Terms

The Encyclopedia of Terms provides supplementary material that might be useful for understanding the other parts of the training materials. In particular, the Guidelines for Informing Policy via Data contains multiple links to the Encyclopedia of Terms. You may also find other uses for this encyclopedia outside of the Metagora context. For this reason, encyclopedia entries are listed here in alphabetical order.

Please note that Metagora uses Wikipedia for entries in the Encyclopedia of Terms according to a strict policy. First, a qualified professional - a person with extensive experience with and an advanced degree in the general topic of the encyclopedia entry - has reviewed the Wikipedia entry and determined the information to be valid and well-written. Second, the Wikipedia entry has been modified from the original context to make it appropriate for use here. Finally, additional or alternative sources of information have been used when possible. As Wikipedia is continuously open to change, Metagora does not endorse the current version of the Wikipedia entry where it differs from the text given in the Metagora entry.

# A B Ca-Cn Co-Cu D E F G H I K L M N O
Pa-Pe Pi-Pr Q R Sa-Sr St-Su T U V W X-Y-Z printable

123 Technique
1-2-3 Technique

The first phase of the 1-2-3 Technique involves a household-based survey on employment and unemployment. The survey is designed to study the labour market and to build the sampling frame for the second phase of the survey. That survey specifically aims to identify informal activities that are accomplished at home. During the second phase of the 1-2-3 Technique, a survey of businesses is performed. Finally, the main sample of the first phase also provides the sampling frame for the third-phase survey, which is a household-expenditure survey related to the informal employment sector. As part of the Metagora project, specific modules on governance and democracy were added to the three types of surveys described.

Further information on the 1-2-3 Technique can be obtained as follows:

1. Information on the Metagora-specific activity related to the 1-2-3 surveys can be found at www.metagora.org.

2. The role of DIAL in the 1-2-3 Surveys can be discussed with François Roubaud – IRD UR DIAL « Développement, institutions et analyses de long terme », 4 rue d’Enghien, 75010 PARIS, France. Tel.: +33 (0)1 53 24 14 76, Fax: + 33 (0)1 53 24 14 50, roubard at dial dot prd dot fr.

Abuse
Abuse

The Mexican survey focuses on a wide range of abuses: from common and "light" violations to less common and more "severe" ones, carried out against the population at large by law enforcement bodies.

When defining the content of the survey and questionnaire to be implemented, a consultation process was conducted by Fundar, Centre for Research and Analysis. This included meetings with other NGOs, the Mexico City Human Rights Commission, and selected experts in human rights, security issues, penal law and related fields. In-depth interviews with police officers, and with individuals who had experienced contact with relevant authorities, were also organised. From this consultation process, it emerged that abuses on behalf of public security forces in the Federal District materialise in numerous forms of law infringement and human rights violations, which extend from minor abuses to more severe practices.

The study thus covers a wide range of abuses: irregularities, abuses of power and acts of ill-treatment. Although the degree of severity of these abuses varies, they share a common characteristic: since they are all carried out by law enforcement agents, they weaken the police and justice systems and do not allow Mexico to reach higher levels of democracy, governance, and respect for human rights.

Although in the human rights vocabulary there are distinctions between the terms “irregularity,” “abuse of power” and “ill-treatment,” limits between one category and another are not always so clear and obvious. A major objective of the study was to obtain evidence-based information on the magnitude and characteristics of such abuses in order to better inform policy-making to enhance democracy, governance, and human rights issues. Thus, throughout the Mexican activity of the Metagora project, the terms “irregularities,” “abuses of power” and “ill-treatment” were considered as one aggregated category: abuses.

Working definition of abuses: Irregularities, abuses of power and ill-treatment

The study refers to two types of abuses: physical and non-physical. Whereas physical abuses are rather self-explanatory, and explicitly outlined in the study by a series of questions starting with “were you hit or physically harmed?”, non-physical abuses include “threats to hurt the person or relatives, threats to accuse someone on false grounds, to ask for money, to compel someone to confess or give information, to insult or humiliate someone, not to be assigned a legal representative when indicted,” etc. For further information, please consult the questionnaire.

During the preparatory phase of this study, international and national legislation and jurisprudence, as well as documents and studies published by various organisations and Human Rights Commissions (both national and of the Federal District) were studied. This information, along with a large consultation process with stakeholders and experts, contributed to the framing of a working definition of abuses, which include irregularities, abuses of power and ill-treatment.

Are considered abuses:

Not allowing a person under arrest or judicial process to exercise his/her rights: i.e., not being allowed to make a phone call to family members or a lawyer, not informing a person of the reasons for his/her detention or of the charges against him/her, not allowing the person to receive medical attention when needed, not allowing a person to include as much proof as desired in his/her file, exerting pressure on witnesses, etc.

When perpetrated by the authority (public agents): extortion, theft, insults, intimidation, all kinds of threats, discrimination, retaining documents as a means of pressure, not accepting a person’s deposition or right to report a crime, unlawful entry, arbitrary detention, forced or involuntary disappearance of persons, homicide, injuries and acts of torture.

Conditions of detention, when relevant: i.e., enquiring whether detention cells are small or overpopulated, prisoners are kept in prolonged solitary confinement, conditions are unhygienic, medical facilities are poor, distribution of food is irregular, prisoners are denied all privacy, detainees are not separated according to their legal status, etc.

Are NOT considered abuses:

Deprivation of liberty as a result of a legal sanction, abuses carried out by a person other than a public agent, such as cases of domestic violence, and/or failures on behalf of the authorities in the administration of justice.

Age-sex Pyramid
Age-sex Pyramid (Population Pyramid) [1]

Example: Population of Laos by Age and Sex, 1995, 2005 and 2020.

www.nsc.gov.la

There are many different ways to graphically present population data. The most important demographic characteristic of a population is its age-sex structure, and the use of an age-sex pyramid, also known as a population pyramid, is considered the best way to graphically illustrate the age and sex distribution of a given population.

An age-sex pyramid consists of two horizontal histograms joined together. It displays the percentage or actual amount of a population broken down by gender and age. The five-year age increments on the y-axis allow the pyramid to vividly reflect both long-term trends in the birth and death rates, and shorter-term baby-booms, wars, and epidemics.

The fertility rate of a population is the single most important influence on the shape of a population pyramid. The more children per parent, the broader will be the base of the pyramid. The median age of the population will also be younger. While mortality will also have an influence on the shape, it will be far less important an influence than fertility, but somewhat more complex. One would assume that lower mortality rates in a population would result in an older age distribution. However, just the opposite is true: a population with lower mortality rates will display a slightly younger age distribution. This is due to the fact that any disparities in the mortality rates of a population are more likely a result of variations within the younger age groups, usually infants and children.

There are generally three types of population pyramids created from age-sex distributions: expansive, constrictive and stationary. Examples of these three types of population pyramids appear at the end of this report. Definitions of the three types follow.

Expansive population pyramids show larger numbers or percentages of the population in the younger age groups, usually with each age group smaller in size or proportion than the one born before it. These types of pyramids are usually found in populations with very large fertility rates and lower than average life expectancies. The age-sex distributions of Latin American and many Third World countries would probably display expansive population pyramids.
The following figure is an example of such an age-sex pyramid. This pyramid of the Philippines shows a triangle-shaped pyramid and reflects a high growth rate of about 2.1 percent annually.
Source: http://z.about.com/ (December 27 2006).
Constrictive population pyramids display lower numbers or percentages of younger people. The age-sex distributions of the United States fall into this type of pyramid.
In the United States, the population is growing at a rate of about 1.7 percent annually. This growth rate is reflected in the more square-like structure of the pyramid. Note the lump in the pyramid between the ages of about 35 to 50. This large segment of the population is the post-World War II baby boom. As this population ages and climbs up the pyramid, there will be a much greater demand for medical and other geriatric services.
Source: http://z.about.com/ (December 27 2006).
Stationary or near-stationary population pyramids display somewhat equal numbers or percentages for almost all age groups. Of course, smaller figures are still to be expected at the oldest age groups. The age-sex distributions of some European countries, especially Scandinavian ones, will tend to fall into this category.
Germany is experiencing a period of negative growth (-0.1%). As negative growth in a country continues, the population is reduced. A population can shrink due to a low birth rate and a stable death rate. Increased emigration may also contribute to a declining population.
Source: http://z.about.com/ (December 27 2006).

Population projections, or percentages of population growth or decline over periods of time, can also be plotted and displayed on a pyramid along with the current or historical population figures, thus allowing for easy comparison of future or historical trends. This type of pyramid is especially dramatic when large, consistent increases or decreases occur.

As an example, in the figure given at the beginning of this encyclopedia entry, the age-sex distribution of the population of Laos (Lao People's Democratic Republic) is given for 1995, 2005, and 2020 (the last being a demographic projection). The changes indicate that the population pyramid is becoming less expansive over time.

1. This definition is based on http://geography.about.com/library/weekly/aa071497.htm and www.health.state.pa.us/hpa/stats/techassist/pyramids.htm.

Analyzer
Analyzer

Human Rights Data Analysis Group (HRDAG)

Human rights groups collect data containing details of human rights abuses from various sources, including medical records, newspaper articles, witness testimonies, letters, interviews, and official reports and documents. Analyzer is used to collect, maintain and analyse that data. The Analyzer database relies on a coding system for the data; that coding system is based on the "Who did what to whom" model.

Analysis of the overlap between sources of data, i.e., individual data-collection projects, allows for the use of multiple systems estimation to estimate a count of abuses within a particular geographic area or political context.

Analyzer is a free, open-source project developed by HRDAG in partnership with the American Bar Association Central European and Eurasian Law Initiative (ABA CEELI), The John D. and Catherine T. MacArthur Foundation, and the Open Society Institute.

Further information on Analyzer can be obtained as follows:

1. Downloads of Analyzer can be found at Sourceforge at http://sourceforge.net/projects/hrdag-analyzer/.

2. The Human Rights Data Analysis Group provides support for using Analyzer and can be contacted at info at hrdag dot org.

Assumptions
Assumptions

statistics

data

public policy

Data collected from a subset of a population cannot be considered representative of that population unless the subset of the population from which the data were gathered is a random sample of that population. For example, sometimes an opinion poll is given to the readers of particular magazine. The statistics developed from that opinion poll represent only the viewpoints of the readers of the magazine who chose to take the poll, not the entire population that has access to the magazine, or even the entire pool of readers of that magazine.
When a statistic is created from collected data (for example, the average salary of adult males in the European Union), a confidence interval is usually included in order to provide the reader with an understanding of the margin of error for that statistic. The confidence interval is usually found by multiplying the calculated standard error for the statistic by a constant determined by the level of confidence desired (e.g., for a 95% confidence interval that constant is 1.96). The statistical assumption made when such a confidence interval is calculated is that the data used to create the statistic have a relatively symmetric distribution. The more skew the distribution of the underlying data has, the less valid the statistical assumption of symmetry becomes and the less valid the confidence interval is.

The important lesson is that if the statistical assumptions underlying an analysis are wrong, that analysis may not be valid. Common causes of violations of statistical assumptions include bias, methodology errors, lack of random assignment in the design of an experiment, and lack of random sampling for a survey.

Further information on assumptions can be obtained as follows:

1. From www.thefreedictionary.com/assumption (19 December 2006).

2. Sources for this encyclopedia entry include Wikipedia (accessed 19 December 2006) [disclaimer]; and Helberg, Clay, "Pitfalls of data analysis," from Practical Assessment, Research & Evaluation (1996) and obtained from http://PAREonline.net/getvn.asp?v=5&n=5 (accessed 19 December 2006).

Back-Translation, Translation
See 'Translation, Back-Translation' Below

Barplot
Barplot

Example: Number of human rights violations per type of non-physical ill-treatment

The survey results correspond to 2,300,000 contacts with police forces experienced by 1,600,000 persons last year (México City D.F., 2005).

In statistics, a barplot is a generic graph that uses bars (rectangles) to show the distribution of data representing a population characteristic or a set of population characteristics. There are many types of bar diagrams, but a main distinction between them is the level of measurement of the population characterstic being displayed. For example, histograms are a type of barplot.

In the example above, the data are categorical: mainly, the number of human rights violations per type of ill-treatment. For displaying categorical data such as these, the bars can be vertical or horizontal, and are usually non-adjacent.

The most widely used bar plots are: one bar for each of the categories of some population characteristic (simple chart, like the one above); the representation of several categories within the same bar (stacked or composed, as given in the first graphic below); and several bars presented together (clustered) to represent groups of population characteristics to be compared (as in the second graphic below).

Canada-Ontario Agreement

Sustainable Energy Development Office

Stacked barplots can also be given in percentages. In those cases, all bars have the same length, allowing easier comparison of the proportions of different characteristics amoung bars. An example is given below.

Statistics Canada

All kinds of barplots suitable for categorical data may be used to represent quantitative data, but histograms cannot be used to represent categorical data.

Bias
Bias

data

The basic definition of statistical bias is as follows: the bias of an estimator (statistic) is how far the average statistic lies from the parameter it is estimating. In other words, if we imagine we could repeat a survey over and over again, and use the same method for each acquired sample to create the same statistic, then we expect the different values for the statistic to be randomly distributed around the parameter we are attempting to estimate. Bias occurs if those estimates for the statistic are systematically lower or systematically higher than the parameter value.

As an example: Let's say we wish to estimate the number of times a police officer requests a bribe in the course of a working day in a particular city. If we take a random sample of police officers from that city, and ask them directly how many bribes they request per working day, it is likely that the police officers will not be willing to tell us the true number of bribes requested. The estimate created from the data we collect will therefore be an underestimate; in other words, the estimate will be biased downward, or lower than the true average number of bribes requested by police officers in the course of a workday.

Let's say, instead, we pick a random sample of police officers and follow them around for a day, keeping track of the number of bribes we observe. It is likely that the police officers' behaviour will be different due to our observation; perhaps they ask for fewer bribes when watched. Again, then, the estimate created from the data we collect will be an underestimate.

Another way in which an estimate can end up biased is via data collected from a non-random subset of a population of interest. Returning to the example of the police officers, let's say we decide to follow a sample of police officers for a day, but pick those police officers by asking for volunteers. It is likely that the volunteer officers are fundamentally different from the non-volunteer officers; the volunteers may be less likely to bribe or behave inappropriately during the course of their duties. For that reason, the estimates we create from the data collected via the volunteer police officers will most likely be biased downward, as the worst of the bribers have little probability of entering our sample.

Finally, bias can occur because of bad questionnaire design, meaning bad question wording or some other systemic issue with a data-collection effort. For example, if we decide to interview the police officers of our city to determine their bribing propensity, but we word our question in a negative, condemning tone, they are less likely to be honest about their bribing than if we word the question in a neutral or supportive tone.

In summary, bias can be introduced into an estimate during any stage: developing a research project, picking a sample to survey, developing a questionnaire, or later in the process. Researchers must therefore be careful to consider sources of bias and do their best to mitigate those sources.

For more information about statistical bias, please see the following resources:

1. Wikipedia [disclaimer]

2. Statistics Glossary

3. Statistics Canada

4. A New View of Statistics

Bottom-up approach
Bottom-up Approach

Metagora

bottom-up approach

Metagora

democrative governance

human rights

statistical

A bottom-up approach is not always necessary for conducting human rights and democractic governance measurement exercises; but it is valuable in providing reliable and useful results. Metagora advocates that in the field of democratic governance and human rights, sharing information is essential if it is to be efficiently used in policy-making. Indeed, one of the most frequently cited advantages of the bottom-up approach is that it promotes and increases “ownership” of these kinds of exercises.

The Metagora project shows that that bottom-up and top-down approaches can complement each other. For instance, a major benefit of global top-down approaches is that they facilitate comparisons, thus providing investors, donors and other bodies with indicators on governance. However, top-down approaches are relatively unsuited for monitoring and evaluating national and local policies or strategies aimed at improving human rights and democratic governance. Often excessively aggregated and generalised, top-down indicators fail to take into account the specific contexts of individual countries, and thus the information available does not provide relevant data upon which targeted policies can be created and developed. A major limitation of bottom-up approaches is precisely that they usually fail to facilitate international comparisons. Metagora was thus conceived as a necessary and useful complement to these top-down approaches, more than as a competing alternative.

Boxplot
Boxplot

Example: A Comparison of Statistical Estimates of Violations in Peru

Source: Science and Human Rights Program, American Association for the Advancement of Science.

A box plot is a graph that characterises the pattern of variation of the data. The plot simultaneously displays several measures of central tendency (what the “average” or “middle point” of the data is) and dispersion of the data (how spread out the data are).

The box plot provides the following information:

the position of the median;
the 25th and 75th percentiles (the 1st and 3d quartiles; these are the sides of the box); and
lines extending from the sides of the box as far as the minimum and maximum values.

Sometimes these lines will extend no further than one (or 1.5) inter-quartile range below the 1st quartile and above the 3rd quartile; in this case, points outside the lines will be individually identified.

CADT
See 'Certificate of Ancestral Domain Title' Below

Capacity Building
Capacity Building and
Skills Transfer

Capacity building

poverty

Skills transfer

There are many different types of capacity-building efforts, primarily determined by the community, group or organisation involved in the efforts. Those efforts include training, human-resource management, organisational development, the strengthening of communities and social networks, conducting research and coordinating alliances.

Capacity building is generally carried out by intergovernmental organisations, such as UNDP, private sector consulting firms and non-governmental organisations (NGOs). Irrespective of the processes and strategies used to build capacity, this term can be applied to interventions that have changed an organisation’s or community's ability to address development issues by creating new structures, approaches and/or values.

Cartesian Coordinate System
See 'X-Y Coordinate System' Below

Certificate of Ancestral Domain Title
Certificate of Ancestral Domain Title (CADT)

Certificate of Ancestral Domain Title (CADT)

Indigenous Peoples Rights Act (IPRA)

indigenous peoples

human rights

indigenous peoples

CDHDF
Comisión de Derechos Humanos of Mexico City (CDHDF)

The CDHDF and its powers

The Mexico City Human Rights Commission (CDHDF) is the organisation in charge of investigating complaints and reports of alleged violations of human rights when they are attributed to any authority or public servant that has a job, position or commission in the pubic administration of Mexico City or in the law-enforcing organisations that have local jurisdiction in Mexico City.

The President of the CDHDF, also known as the Defender of the People, is assigned by the Mexico City Legislative Assembly (Asamblea Legislativa del Distrito Federal, ALDF), and his authority is autonomous, that is, it is not subject to any authority or public servant.

The CDHDF works according to its own laws and internal regulations. As stipulated in Article 17 of the Mexico City Human Rights Law, the powers of the CDHDF are to:

Receive complaints of alleged violations on human rights.
Know about and investigate written requests by the people of alleged violations on human rights in the following cases:
1. By acts or omissions of an administrative matter by public servants or by the Mexico City authorities, which third article of this Law refers to.
2. When a person or any social agent commits a crime with the consent of a public servant or local authority of Mexico City; or when the latter refuses, on no grounds, to exercise the obligations that they have in relation to these crimes, especially when they affect people’s physical integrity.
Make conciliatory proposals between the people who complain and the authorities or the public servants allegedly responsible, to immediately solve the problem when possible.
Make autonomous public recommendations, reports and complaints before the corresponding authorities.
Compel adherence to human rights in Mexico City.
Suggest to the different authorities in Mexico City, alterations in legislative decisions, and administrative practices that, according to the CDHDF, would lead to better protection of human rights.
Promote the study, teaching and promotion of human rights in its territorial area.
Issue its internal rules and regulations.
Make and orchestrate preventive programmes regarding human rights.
Ensure that the conditions of the people deprived of their freedom in detention, internment and social re-adaptation centres of Mexico City conform with the law, that the individuals’ human rights are fully respected, that medical examinations are performed on prisoners or those arrested when there are allegations of mistreatment or torture, and that the results of the revisions performed are reported to the appropriate authorities. These powers have no prejudice regarding the Human Rights National Commission (CNDH); coordination mechanisms will be used to exercise these powers.

Brief History of the CDHDF

Established on 30 September 1993, the Mexico City Human Rights Commission is the newest public organisation created to protect human rights in Mexico and is based on Article 102, section B of the Mexican Political Constitution.

The Defender of the People first appeared in Sweden at the beginning of the 19th century. The office exists now, in many variations, in many countries of the world. The Defender of the People is a mediator who seeks conciliatory ways to resolve conflicts. He/she is completely autonomous, and has the authority to resolve cases quickly, foregoing long judicial proceedings.

The People whom the CDHDF Serves

Any person that considers that his/her or another person’s human rights have been violated, regardless of his/her social condition, nationality, race, religion, sex, age, marital status, etc., can go to the Mexico City Human Rights Commission.

It is not a requirement to have a lawyer or an agent to make a complaint. A complainant only has to report, in either written or oral form, why he/she believes his/her rights were violated and present any evidence he/she might have. All information presented by the complainant is kept confidential.

All services are direct, free of charge, and operate on a 24h basis all year round.

Legal Authority of the CDHDF

(Article 18 and 19 of the Mexico City Human Rights Commission Law):

The Mexico City Human Rights Commission cannot become involved with cases regarding:

Acts and resolutions of electoral organisations or authorities;
Resolutions regarding jurisdictional matters;
Issues regarding working matters; and
Consultations posed by the authorities, citizens or other entities, on the interpretation of constitutional dispositions and of other juridical rules and regulations.

For the purposes of the above Law, jurisdictional resolutions are:

The final sentences that conclude the requests;
The interlocutory sentences that are brought in during the process;
The court orders and agreements passed by the judge, court staff, court or law-enforcing organisation, with a previous evaluation and juridical or legal process carried out before it is issued; and
Cases similar to those above concerning administrative issues.

All other acts or omissions of the procedures different to the ones mentioned in the previous sections can be considered to be administrative and, consequently, can be presented before the Mexico City Human Rights Commission.

The Commission does not examine jurisdictional matters.

For further information, please refer to www.cdhdf.org.mx/index.php?id=piwhr

CHRP
Commission on Human Rights of the Philippines (CHRP)

human rights

Protecting and promoting the human rights of all the people residing in the Philippines and Filipinos residing abroad, especially the underprivileged and disadvantaged sectors of society;
Engaging in sustained efforts with organisational integrity and competency in seeking justice; reorienting the agents of the State along human rights norms; advising the State on national policies and standards; catalysing effective and credible partnerships; and working with national and international organisations;
Advocating and monitoring the government's compliance with its international treaty obligations on human rights; and,
Encouraging civil society participation.

The organisation’s programmes and services are organised around four main axes:

Human Rights Protection Programme, which includes Investigation and Forensic Services, Legal Services, Legal Aid and Counseling, Conciliation, Mediation, Human Rights Assistance, and Visiting Services;
Human Rights Promotion Programme, which includes Education and Training, Human Rights Information and Public Advocacy, Human Rights Research and Development, Compliance Monitoring of International Human Rights Standards in Governance, and Web Services;
Human Rights Linkages Development and Strategic Planning, covering Rights-based Planning in Governance, Human Rights Performance System in Governance, Harnessing Competence in Government and None-state Actors for Good Human Rights Practices, the Executive Cooperation Programme, and the Legislative and Judicial Cooperation Programme; and,
Special Programmes, which include Rights-based Approach Application, Barangay Human Rights Action Centre, Human Rights Teaching Exemplars, Child Rights Centre, Women's Rights Programme Centre, and Asia-Pacific Institute of Human Rights.

Within the framework of the Metagora pilot project, the CHRP implemented a pilot survey focusing on the effective implementation of indigenous peoples’ human rights. In this exercise, the CHRP developed a strong collaboration with the Philippines National Statistical Coordination Board (NSCB) and the National Commission on Indigenous Peoples (NCIP). The activity consists of a small but incisive survey-based study implemented in three northern regions of the country with a high concentration of indigenous peoples. The objective of this pilot exercise was to develop evidence-based assessment methods and tools combining quantitative and qualitative approaches. The study aimed to measure four aspects of the rights of indigenous peoples to their ancestral domains and lands: the indigenous peoples’ perceptions and awareness of their rights, the enjoyment or violations of these rights, government measures and customary laws for the realisation of these rights, and the availability of mechanisms for redressing or fulfilling rights.

For further information regarding this pilot survey, please turn to the Synthesis Report produced by the Metagora Coordination Team.

Civil Rights
Civil Rights

Human rights

political rights

rights

the first generation refers to civil and political rights;
the second generation comprises economic, social and cultural rights; and,
the third generation refers to collective rights.

Civil rights are primarily designed to protect the individual against state interference, and are immediately applicable. They include the protection of life and security (i.e. the right to life, prohibition of torture and inhuman treatment or punishment, etc.); the prohibition of discrimination on any ground (such as race, sex, language, religion, political or other opinion, national or social origin, property, birth or other status); the protection of liberty (i.e., prohibition of arbitrary arrest and detention); and a set of freedoms (such as freedom of movement, of marriage, of religion, of peaceful assembly, of association, etc.). Civil rights can therefore be seen as the protections and privileges (rights and freedoms) that protect individuals from the state, thus ensuring their personal liberty.

Though distinct, civil rights and political rights are closely linked; the protection and fulfillment of one depends to a large extent on the fulfillment and protection of the other. Moreover, the distinction between civil and political rights is not always so obvious or clear; sometimes the two overlap.

All human rights are indivisible, interdependent and interrelated: the fulfillment and protection of civil and political rights depend on, and are required for, other categories of human rights.

In international human rights law, civil rights are essentially protected by the International Covenant on Civil and Political Rights (ICCPR), which was drafted in 1966 and entered into force in 1976. Adherence to the Covenant is monitored by the Human Rights Committee. Over time, additional protocols and instruments were created which also aim to protect civil rights.

All States Parties to the Covenant are required to submit regular reports to the Committee on how they are implementing civil and political rights. Such information is provided by self-reporting and, thus, can be limited. The reports provided are examined by the Committee which is composed of independent experts appointed by the United Nations. The Committee then addresses its concerns and recommendations in the form of "concluding observations." In the First Optional Protocol to the Covenant, the Committee was given jurisdiction to examine individual complaints; this is not yet the case with the Committee established to monitor economic, social and cultural rights [1].

1. For further information, please refer to the web site of the OHCHR, http://www.ohchr.org/english/bodies/hrc/index.htm.

Closed-ended Question
Closed-ended versus Open-ended Questions [1]

Closed-ended questions limit respondents' answers to the survey. The participants are allowed to choose from either a pre-existing set of dichotomous answers, such as yes/no, true/false, or multiple choice with an option for "other" to be filled in, or ranking-scale response options. For example, a closed-ended question might ask for a respondent's religion, giving several religion categories (i.e., Catholic, Protestant, Buddhist, Muslim, etc.) and an "other" option.

The most common of the ranking-scale questions is called the Likert scale question. This kind of question asks the respondents to look at a statement (such as "The most important education issue facing our nation in the year 2000 is that all students in their third year of primary school should be able to read") and then "rank" this statement according to the degree to which they agree ("I strongly agree, I somewhat agree, I have no opinion, I somewhat disagree, I strongly disagree").

The advantages of closed-ended questions are:

Closed-ended questions are more easily analysed. Every answer can be given a number or value so that a statistical interpretation can be assessed. Closed-ended questions are also better suited for computer analysis. If open-ended questions are analysed quantitatively, the qualitative information is reduced to coding and answers tend to lose some of their initial meaning. Because of the simplicity of closed-ended questions, this kind of loss is not a problem.
Closed-ended questions can be more specific, thus more likely to communicate similar meanings. Because open-ended questions allow respondents to use their own words, it is difficult to compare the meanings of the responses.
In large-scale surveys, closed-ended questions take less time from the interviewer, the participant and the researcher, and so they are a less expensive survey method. Generally, the response rate is higher with surveys that use closed-ended question than with those that use open-ended questions.

A limitation of closed-ended questions is the assumption that the researcher knows enough about the phenomenon being studied and about the respondents' perceptions to be able to build an appropriate and sensitive set of categories. If that is not true, the responses might be grouped into inappropriate categories or concepts. When using closed-ended questions, the researcher might first have an exploratory survey during which a small sample is asked open-ended questions. The answers obtained can be used to form categories and/or check the researcher's assumptions.

Open-ended questions do not give respondents answers to choose from, but rather are phrased so that the respondents are encouraged to explain their answers and reactions to the question with a sentence, a paragraph, or even a page or more, depending on the survey. If you wish to find information on the same topic as asked above (the future of elementary education), but would like to find out what respondents would come up with on their own, you might choose an open-ended question like "What do you think is the most important educational issue facing our nation in the year 2000?" rather than use the Likert scale question. Or, if you would like to focus on reading as the topic, but would still not like to limit the participants' responses, you might pose the question this way: "Do you think that the most important issue facing education is literacy? Explain your answer below."

The advantages of open-ended questions are:

Open-ended questions allow respondents to include more information, including feelings, attitudes and understanding of the subject. This allows researchers to better access the respondents' true feelings on an issue. Closed-ended questions, because of the simplicity and limit of the answers, may not offer the respondents choices that actually reflect their real feelings. Closed-ended questions also do not allow the respondents to explain that they do not understand the question or do not have an opinion on the issue.
Open-ended questions cut down on two types of response error: respondents are not likely to forget the answers they have to choose from if they are given the chance to respond freely; and open-ended questions simply do not allow respondents to disregard reading the questions and just "fill in" the survey with all the same answers (such as filling in the "no" box on every question).
Because they can elicit extra information from the respondent, such as demographic information (current employment, age, gender, etc.), surveys that use open-ended questions can be used more readily for secondary analysis by other researchers than can surveys that do not provide contextual information about the survey population.
Research has shown that open-ended questions are better for eliciting sensitive information, such as information about sexual assault or drug usage, than closed-ended questions.

Note: Keep in mind that you do not have to use closed-ended or open-ended questions exclusively. Many researchers use a combination of closed and open questions; often researchers use closed-ended questions in the beginning of their survey, then allow for more expansive answers once the respondent has some background on the issue and is "warmed-up."

1. This definition is modified from Types of Questions (accessed 28 December 2006).

Cluster Sampling
Cluster Sampling

one-stage cluster sampling

two-stage cluster sampling

multistage cluster sampling

In cluster sampling, the clusters are the primary sampling unit (PSU’s) and the units within the clusters are the secondary sampling units (SSU’s). It is important to keep these two levels in mind when calculating standard errors from cluster samples. If a cluster sample is analysed as if it were a simple random sample, the reported standard errors would probably be smaller then they should be. That would give the impression that the survey results are more precise than they really are. Whereas stratification often increases precision of the estimation compared with simple random sampling, cluster sampling often decreases it. That is because units in a cluster tend to be more similar than elements selected at random from the whole population. When using cluster sampling, it is usually necessary to increase the total sample size to achieve the same precision as in simple random sampling. Nevertheless, there are cases where cluster sampling is useful.

The main reason for using cluster sampling is that it usually much cheaper and more convenient to sample the population in clusters rather than randomly. In some cases, constructing a sampling frame that identifies every population element is too expensive or impossible. Cluster sampling can also reduce cost when the population elements are scattered over a wide area. Suppose you want to survey school children of a certain age in a specific area. If you drew a simple random sampling of school children, you might have to visit all schools in the area to interview your sample. With cluster sampling you could first select the schools to be included in your sample, and then select school children within each of the selected schools. That would probably reduce the number of schools you have to visit and therefore reduce the cost of data collection. In this example, the schools are what are sometimes referred to as natural clusters. In other cases, the population may be widely distributed geographically, and then cluster sampling, where the clusters consists of geographical areas, could reduce the number of areas that need to be visited. A smaller number of areas that need to be visited could reduce travel expenses and also make possible more efficient supervision of the fieldwork.

For more information about cluster sampling, see: Sarndal, C.E., Swenson, B., and Wreman, J.H., Model Assisted Survey Sampling, Springer-Verlag, New York, 1992.

Coding
Coding

controlled vocabulary

data

human rights

Coding is a necessary step in the development of statistics from qualitative data sources. Coding is also sometimes used in the field during a survey, for collecting quantitative information. In that case, the controlled vocabulary/data categories are determined prior to data collection, and the interviewer is responsible for coding a respondent's qualitative information and recording the appropriate code on the questionnaire.

Cognitive Interviewing
Cognitive Interviewing [1]