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Quels les critères essentiels du choix des données (Variables en études)

Sharing the limitations of your M&E strategies may be hard for a data scientist who wants to achieve perfect results but it shows that we are human and we can make mistakes .

Collect, use and present your data accurately. Be clear about how your M&E processes work and be honest about any limitations to your work.

Honesty is a key to building trust, an Honest report provides for more opportunities from funders.

honest with all data collected is a priority for all who are involve

Honesty is key in data collection as it tends to eliminate Biases.

False information leads to wrong decision-making. So, providing false data or information it is not only a crime, but also shows how bad professional we are, professionals without the sense of responsibility. The Honesty principle help us to avoid many problems.

Sadly, some think of ethics as a process that drags data collection. Honesty is a virtue in research that cannot/should not be downplayed.

We must be confident that the data which we and our entire team members supply to public or main clients are as much accurate as possible . This is because of the reason that the company honesty totally lies on that for sure for future endeavors.

Speaking the truth and act truthfully is all about being HONEST your action should reflect what you say and must be truthful too. It is good to be honest even at your work place and with the work you are been given to do by presenting the right or correct data , manage the work correctly and so .

The M&E professionals should always ensure that their data is honestly and clearly collected, managed, analyzed and presented. In other words, to avoid unethical issues to interfere in the quality of collected data, the M&E representatives should serous enough not to lie and present false conclusions about their data.

The M&E professionals should always ensure that their data is honestly and clearly collected, managed, analyzed and presented. In other words, to avoid unethical issues to interfere in the quality of collected data, the M&E representatives should serous enough not to lie and present false conclusions about their data.

The M&E professionals should always ensure that their data is honestly and clearly collected, managed, analyzed and presented. In other words, to avoid unethical issues to interfere in the quality of collected data, the M&E representatives should serous enough not to lie and present false conclusions about their data.

The M&E professionals should always ensure that their data is honestly and clearly collected, managed, analyzed and presented. In other words, to avoid unethical issues to interfere in the quality of collected data, the M&E representatives should serous enough not to lie and present false conclusions about their data.

The M&E professionals should always ensure that their data is honestly and clearly collected, managed, analyzed and presented. In other words, to avoid unethical issues to interfere in the quality of collected data, the M&E representatives should serous enough not to lie and present false conclusions about their data.

The M&E professionals should always ensure that their data is honestly and clearly collected, managed, analyzed and presented. In other words, to avoid unethical issues to interfere in the quality of collected data, the M&E representatives should serous enough not to lie and present false conclusions about their data.

In simple terms this can apply to being real or realistic. Therefore, the monitoring and evaluation team must adhere to a high level of integrity through providing accurate and reliable data. Furthermore, the team is also expected to report both the advantages and disadvantages encountered in due of collecting information/data.

Be truth and honest when collecting data

If remaining honest in your m&e plan includes, declaration of any conflict of interest, any limitation of the work and the accuracy of the results, the employment of an independant actor Can therefore be part of one's solution to solve some of this problems.
Honesty will make your result overview clear for everyone and will give to your organisation some respect from those who will use your results

Data accuracy is key especially in organizations where leadership demand for successes of the projects. in some cases M&E officers report wrong data to justify relevancy, efficiency, and coherency of projects

I,m truly an honest person who wants to learn this precious opportunity

all in all I,m good because of my Accuracy and good data quality and also very good I think

I hope to finish with success

Whenever you data collect you must be honest and loyal and to protecting the data that will lead to your being trustworthy
You must be able to resolve the conflict organization if it comes up

Whenever you data collect you must be honest and loyal and to protecting the data that will lead to your being trustworthy
You must be able to resolve the conflict organization if it comes up

If you and your team carry out M&E processes without the required technical or cultural skills, you might unintentionally cause harm or present data that does not live up to the honesty principle.

Honesty should be in all elements of research; especially in the description of the techniques and procedures used, data collection, making use of and referencing the work of other researchers, making assertions that are supported by evidence and communicating accurate interpretations.

Communicating accurate findings help in devising the appropriate strategies in solving a problem. when findings are communicated accurately with its associated limitations, it helps build further research to build on limitations and strengthen existing strategies put in place to solve the problem.

Well understood

Yeah it means when we collect a data in any field we should not change its result we must be honest and show the exact result

Honesty implies to the collection, use and presenting of your data accurately. This therefore, implies to being clear about how your M&E processes work and being honest about any limitations to your work. Hence data from M&E processes is expected on the other hand to be as close as possible to the pure truth.
Some of the ways to ensure that your M&E team is abiding to the honesty principle can be seen as follows;
Ensuring that the findings from your M&E are accurately represented. This means that you should not present data that you know is inaccurate. However, it also means that you will need to to constantly check the accuracy of your data.
Furthermore, ensuring that the findings from your M&E are accurately represented. This implies that the M&E team presents conclusions that are strongly worded and simply accurate.
Sharing the limitations of the M&E strategies is yet the other way to ensure that your M&E team is abiding to the honesty principle. This implies that the M&E team will not be able to collect perfect, absolutely complete data. Nor will you be able to state conclusions with complete certainty. Hence be honest about these limitations with donors, beneficiaries, or any one who might be interested in your work, ideally share these limitations before your project starts, so that people do not develop unrealistic expectations.
Share any areas where you might have a personal or professional interest in a certain outcome. This implies that you or your organization may gain something useful if a certain outcome is reached.

this principle is good for M&E staff to understand the Working capacities
this restricted that any finding must be represented and data represented must be accurate

very interested

very interested

The integrity of this course is important to me at runtime.

الأمانة باختصار هي دمج بين الموضوعية والمصداقية وعدم الانحياز وبعض الخصال التي ان تؤدي بمجملها الى الحقيقة ونقل الواقع كما هو وبالاضافة الى عدم التهاون بالقوانين مع الأخذ بعين الاعتبار توفر الرحمة والقفز فوق بعض معسِّرات العمل لاكمال عملية الالتزام بحفظ البيانات وعدم الخلط لجعل بعض البيانات توحي بعدم المصداقية او النقص والانتقال الى جعل البيانات كما هي مع شرح الحالة التي تحيط بهذه البيانات

generally, honesty is a great virtue and should always be implemented throughout a project. as we go on about our project we should ensure honesty as much as possible. do not lie about the project goal, do not lie or twist the truth to your benefit, and do not lie to the donors. most important of all never lie about the outcome of your project.

This is M&E concern that we refer as Ethical principles that require that all finding must be shared
and all data represented must be accurate and clear

Honesty is really one key factor in collecting and using data!

The data collected should be cleared and answer the research questions (while the research questions themselves should also cover the purpose of the research or evaluation). Vague questions will lead to poor data being collected.

Honesty is essential in monitoring and evaluation (M&E) because it ensures that data is accurate and reflects the true state of the program or intervention being evaluated. Honesty involves being truthful and transparent about the data that is collected and reported, including any limitations or uncertainties associated with the data.

In M&E, honesty is important for several reasons. First, it helps to build trust between the program or intervention being evaluated and stakeholders, including funders, partners, and beneficiaries. When stakeholders know that the data they are receiving is accurate and reliable, they are more likely to support the program or intervention.

Second, honesty is important for ensuring that programs and interventions are effective. If data is manipulated or misrepresented, it can lead to incorrect conclusions about the effectiveness of the program or intervention. This can result in resources being allocated to ineffective programs or interventions, which can be detrimental to beneficiaries and stakeholders.

Finally, honesty is important for accountability. M&E is used to hold programs and interventions accountable for their performance and to identify areas for improvement. If data is not honest or accurate, it can make it difficult to identify areas for improvement and to hold programs and interventions accountable for their performance.

In summary, honesty is a crucial element of M&E. It ensures that data is accurate and reliable, builds trust with stakeholders, promotes effective programs and interventions, and supports accountability.

M&E guys should prove themselves honest to their organization by providing continuously accurate and valid data from the intervention's process monitoring and collecting data on outcome indicators, as the management mostly makes decision based on the collected and disseminated data by M&E, therefore the facts and reality should be included in the M&E data and report and do not be ignored.

honesty is very important for every thing.

Honesty principles in practices means data needs to be transparently collated, managed, analyzed and presented. This is applicable to each and every part of the processes mentioned and most importantly reports should be honestly presented.

Honesty as a principle of M&E provides the accuracy both in Data collections, limitation strategies, finding representation and other interests professionally or personally

Of course without honesty you become biased and May result to wrong findings in any research carried out.

Honesty is one of the aspects that is usually difficult to maintain. my question is; how do you maintain honesty in a crisis environment ??

Increase the value of your business by reducing the perception of risk.
Not only is an honest person respected by all parties, but being fully transparent can increase the value of your business(by reducing the perception of risk) and make your business easier to sell. Being honest reduces the buyer’s perception of risk, which means they may be willing to pay mor…
Save yourself time by being honest.
Being honest also saves you time from having to remember any half-truths that may have been told. It gives you freedom because you have nothing to hide.

Conflict of interest is one of the areas that a lot of practitioners fail to be honest in while implementing programs

The M&E professionals should always ensure that their data is honestly and clearly collected, managed, analyzed and presented. In other words, to avoid unethical issues to interfere in the quality of collected data, the M&E representatives should serous enough not to lie and present false conclusions about their data.

Honest on presenting data is not on M&E only it should be on any kind of information told or written.

it is important for ME specialists to avoid preconceived judgments based on their colleagues' or boss assumptions or suggestions simply to please them. Honesty and unbiased decisions are the keys to success.

Honesty in M&E will have integrity on your data and the report thereafter. It is better to present the real outcomes of the data than manipulate it to fit individual bias or appeasement policy

It is always good to be honest when planning for M&E, when implementing projects and when reporting. Lies are always inconsistent and they lead to donor flight, wrong policy directions and they also foster incompetence.

It is important to be mindful when collecting data its use and presenting the data accurately. It is equally important to let all stakeholders know of the limitations and challenges that one may face in the course of the process.

I think honesty is fundamental in Data strategies, and the single most important thing that drives our interactions with stakeholders, when we so daringly need to impress.

Honesty mean that for a successful employee we need to follow to important issues.
the one is our knowledge professionalism
the second one is our committment it means honesty and loyality

Honesty mean that for a successful employee we need to follow to important issues.
the one is our knowledge professionalism
the second one is our committment it means honesty and loyality

It is a very relevant point. To be honest it is always good because is related to your integrity, and manipulating the data scenario can impact negatively the decision.

Honesty is very necessary especially in field of data management, not being honest with your data's usually has a comeback effects that is not always pleasant to the recieving end. It could tarnish ones image and degrade one to the full

Honest data use goes far beyond simply publishing knowingly inaccurate data; it is really important to represent data in such a way that your audience will not misunderstand your findings. If you unintentionally make a claim that your data cannot support, this could still be considered dishonest, regardless of your intentions.

Honesty is one of the essential principles of ethical behavior, yes there is need to share limitations of your M&E strategies to the interested parties or stakeholders and preferably at the beginning of the project so that people do not develop unrealistic expectations about the project.

Honesty is about principles and values that everyone does not born with it but leans during life. So, by walking with those principles you will avoid being dishonest wherever you are, mainly on important services like data management because can impact negatively the decisions!

If my organization has collected and analysed data with a conclusion that is against a certain firm which is not the sponsor of the research. Would it be advisable to present the research to them first before presenting it to the public? I think it is better to present it to the public first for if it is presented to the firm first it would:

• Bring about undue pressure on my organisation to alter data or conclusion in favour of the firm.

• It would interfere with the impact of the research especially when the firm goes on a charm offensive before you release it to the public.
  Do advice on this aspect.

Honesty forms the foundation of M&E work. It ensures accurate and reliable data, fosters transparency and trust, upholds ethical standards, and facilitates learning and improvement. By prioritising honesty in M&E practices, we strengthen the integrity of evaluations, enhance decision-making processes, and ultimately contribute to more effective and ethical outcomes. Problem for me is when there is a translation involved where the language barrier can influence or affect the honesty of the data collection.

A conflict of interest happens when you or your organization might gain something useful if a certain outcome is reached.

It is very important to have integrity and focus on building a long lasting relation based on honesty even when it seems not being honest might seem beneficial.

Honesty is very crucial at all times, especial when dealing with data.

Honesty is very important, and I agree that your data collection's limitations and challenges should be informed or presented. Some projects, example 100% condom used project, may not be able to collect the actual usage of condoms from the direct beneficiaries due to different cultures. However, the data can be collected from those who sell or distribute condoms at the shop or public. In this case, the data presentation might be accurate, but if the limitation is mentioned, the readers/audience will understand the represented data and results.

The idea that I found most interesting and had not initially thought of is the need to disclose relationships and potential conflicts of interest with your studies. While I knew that it is unethical to outright lie in your data to support a desired conclusion, such as the example of the pharmaceutical company and lying about the outcomes of the test. However, I had not considered the need to disclose a potential conflict of interest even when the data presented is 100% accurate. I now understand the need to disclose potential conflicts of interest, as hiding them from the public is still an unethical practice. Additionally, I thought the need to ensure that your conclusions are accurately reflected by your data. When presented with data such as that in the example given, it can be easy to see how someone might misinterpreted the data and give an inaccurate conclusion such as counseling programs help lower adolescent pregnancy rates. That is why it is important to consider what your data actually shows, in this case a correlation between the two. Correlation does not equate to causation.

It is crucial to ensure data consistency before any presentation and to be well-informed about the process of data collection, transformation, and usage.

Honesty is very needed in how we get and present actual data that also influence the quality and information we convey to other relevant parties.

There is indeed often a conflict of interest regarding being honest when dealing with program data. This is often so, when M&E is constantly pressured by implementing teams or programs teams that are constantly needing to achieve or are trying to show that they have achieved the project goals.
It then is important to ensure that honesty of paramount importance when presenting data, more especially while working a project team that is abscessed with results either by hook or crook. As M&E, we really ought to give the proper directions so that ethics are adhered to and enlighten teams on how biased and dishonest data could potentially affect or harm the populations we are trying to help.

We have to present the data that are truth. If we present the fake data then it may lead to failure of the project. In other word it can misguided the outcome and impact

I saw the importance of ethics in the data collection phase

I saw the importance of ethics in the data collection phase

without data we cannot do anything however data can cause many legal issues when used incorrectly and also cause embrassment to individual, when using data that is confidential ensure that the data is no persimable to unathorised persons. we apply honesty and integrity .

Honesty issues occur all the time especially during reporting of project outcomes and findings. in Many cases, project are not as planned. Donors have rigid contracts with organizations, and organizations either want to remain working, or do not want to be considered incompetent end up reporting something very far from the actual.

It all has to start from how a program is planned, and all programs must give room for modifications where there is need. Without all these, people will be forced to report false data.

Well for me, I take accurate data, and report what I have found.

The implication is that we have to replan

Honesty is a very important part of data collection, analysis and presentation, it can affect the aims and objectives of the program.

Honesty is a very important part of data collection, analysis and presentation, it can affect the aims and objectives of the program.

It's very important to honest with data, however i don't understand the example given with the pharmacy company, why publishing that the drug is effective if the date is accurate, could be unethical

When we collect data ensure that every piece of information fill correctly and honestly no fraud and false information filled , this is also ensures that if anyone one told you something personal, and do not want to fill any fill because he share his personal thoughts with you by faith ensure that if you see any new or something interesting views or something touches your mind or heart please consider it if you make interest in any of family or other things collect in your data.it may also consider that your M&E is concise and everyone can understand easily

it's not enough to till the truth the circumstances of data collection and the personnel involved should be clarified for more transparency

its very important for you as a project manager to inform your participants what they are participating

if you are not honest you cannot work any people

Collect use and present your data accurately.
You understand that lying is morally wrong and can couse damage.
It's significantly to don't present the data that you know it's in accurate.

Provide skilled professional service.
You should have to ensure the cultural and technical skills to carry out M&E process.
Like
Mapping stake holder needs
Storing data securely
Designing surveys

Honesty- It is a simple concept but encompasses a few sub concepts such as: data should be accurate, the date should be represented accurately, limitations of strategy should be communicated clearly and share personal and professional outcomes vividly.

collect use and present your data accurately.
you understand that lying is morally wrong and can couse damage.
ensure that data your data your present is accurate

Collect use and present your data accurately
You understand that lying is morally wrong and can couse damage.
Ensure that the data your present is accurate.

Honesty and integrity are the integral component of M&E

Transparency and honesty is very important in communicating data.

the team need to honesty to present in data

I am totally reflecting on why most organisations offer consultants some contracts to carrry out some market studies or surveys on their behalf. To curb conflict of interest from them

honesty is not credible data, which reflects reality

It is important to be honest, it will safe lots of stress and damages.

It is important to be honest, it will safe lots of stress and damages.

Limitations of data collection and use must take into consideration the area of interests of key stakeholders and the participants of the study.

I love the statement that says If your are not sure of raw data do not use, but what of the case that is external that enter the data

we have to be responsible and positive with what we have collected or our coleections