Science topic

Evaluation - Science topic

Evaluation in all area.
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Evaluation metrics needed
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Dear Muralidhar Patruni . The best research is the one which helps the community more than other researches in all directions.
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I am looking for a study that dealt with the differences between institutions in student evaluation of the faculty. What I am interested in knowing is whether there is a difference between students from prestigious institutions and ordinary universities and colleges, one can perhaps assume that in private and competitive institutions the students will be critical and demanding. But I can't find any evidence or even a comparative study on the subject, I've been searching Google Scholar for a few days now
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Visit also the following useful RG link:
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English language centers in the non English speaking world assess the English of their teachers and professors by using tests that are appropriate for U.S., Canadian, British, Australian environments. These specific contexts at times do not match the academic needs of language centers outside the U.S. or Great Britain for instance
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I think that the best of these tests is the IELTS test because of the test's ability to distinguish between the language proficiency of the testers
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Evaluation for epistemological and ontological differences between different research methodologies and
Evaluate the strength and weakness of variety of business and management research methods
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To study this topic, I think that the comparative research method is useful in these topics
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In the ScholareOne system, after the peer-review is completed, the status changes to "Evaluating Recommendation". How long does this status typically takes before hearing back from the journal editor?
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Ideally, the status "Evaluating recommendation" should not take more than a few weeks. In this stage, the Associate Editor (AE) evaluates the suggestions of the peer reviewers and gives his/her recommendation to the Editor-in-chief (EiC).
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I have created and validated a Campus Climate Identity Survey, as part of my doctoral work at NYU dealing with my home institution and am now looking for collaborators. The survey is validated with the pilot and really designed as a way to get comprehensive data in all the schools in academic health science centers not just the medical school component. Are you looking to gain a comprehensive view of the plight of your staff, students, and faculty at an academic health science center, then I'd love to chat with you.
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thanks for the great information. where does it take place?
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Evaluation metrics in fuzzy systems.
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Any type of error metrics such as MSE, IAE, ISE, ITAE, MAE etc
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As part of my fellowship, I want to evaluate the oral health surveillance system as part of my fellowship. I already read CDC's guidelines for evaluating surveillance systems, but I am still confused about how to assess one. Does anyone have examples of work or reviews done for this type of evaluation?
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For evaluation, following steps to be pin pointed and assessed making some suitable & useful indicatiors. These are - input evaluation, process evaluation, output evaluation, outcome evaluation & impact evaluation. If you analyse critically about logistics required and actually provided, it will give you information about input. mecanism of collection of surveillance data and completeness of collection will tel you about process etc.
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I am on a state oral health department fellowship, and I am severely frustrated with picking an evaluation project. It has been months of literature research, brainstorming, planning, and talking with stakeholders. The topic I want to do is the Sugar Sweeten Beverage invention guide (similar to tobacco cessation 5A's) at the state level. However, I cannot formulate a question, target audience, and data to back up the evaluation. Has anyone done any state evaluation intervention method? Or any pointers? Thanks.
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Clare Mendioro it is important to identify the state of the program (e.g., early stages, well-established, etc.) so that you can propose the proper evaluation form (e.g., implementation study, outcomes-based, impact, etc.). Once those have been established, then you can frame your evaluation questions based on what others who have completed that evaluation form have asked. From the evaluation questions will emerge the necessary target audience and data you will need.
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Hello, I am a graduate student at Arizona State University with the Mary Lou Fulton Teachers College, I am pursuing a M.Ed in Learning Design and Technology, I am currently enrolled in Intro to Research and Evaluation in Education. After completing this weeks reading and formulating a definition of both research and evaluation, and comparing the two, I have a question to pose.
How can empirical data best be used in research and more importantly how can subject and data benefits evaluations, to help measure worth? Is evaluation as cut-and-dried as it seems or is there room for subjectivity?
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Any original data collected on human subjects is empirical (as opposed to getting information from primary and secondary sources to compile a review). Both qualitative and quantitative data qualify as empirical (e.g. qualitative interviews or observations of behavior or quantitative cognitive tests).
It seems as if your question is more directed towards subjective vs objective data collection. Most empirical data collected on human subjects is subjective to some degree, some more than others, no matter if it's used strictly for the purpose of educational assessment or to answer research questions for a research study. For instance, if a teacher or researcher wanted to assess students' writing ability, they would do so with a rubric. A rubric reduces subjectivity by providing a uniform measurement structure, but it in no way eliminates it. This is why for research or high level assessment (high stakes tests), you would be expected to establish interrater reliability my having multiple raters score each paper and then comparing their scores for accuracy.
Qualitative research is, by nature, more subjective than quantitative research because the findings and conclusions are so dependent on the interpretation of the researcher. In most cases a reader or critic can look at qualitative research and conclude they may have had a different interpretation of the data. This is why one of the main tasks of qualitative researchers is to reduce biases and hopefully, reduce subjectivity, so the conclusions are not based strictly on opinion.
In quantitative research, if students' scores rose, by say 15%, then that's not very subjective. It's a fact that that was the case. But there is still subjectivity in that reasonable people can argue about why that increase occured (The intervention? Teacher effect? A faulty research design with a confounding variable? Perhaps the variables weren't properly controlled? Etc.).
If the question strictly deals with subjective assessment versus objective assessment, while most forms of assessment (e.g. constructed response, projects, etc.) include a good dose of subjectivity, some are in fact entirely objective. For instance, a multiple choice math problem is completely objective- one answer is objectively correct and three are objectively incorrect. Quality multiple choice questions, regardless of content area, should be objective (and contrary to common misonceptions, often do assess higher order thinking). This is why multiple choice items are more often used on high stakes tests and in research studies. By reducing or eliminating the subjectivity, the data should be more valid from the start and more straightforward to interpret, and those making use of the data do not have to jump through hoops for additional steps like establishing interrater reliability.
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Hello,
I am a grad student at Arizona State University earning my degree in Learning & Curriculum in Gifted Education. I am enrolled in Introduction to Research and Evaluation. The major assignment in this course is to write a Research Proposal with Literature Review. We are currently discussing the differences in Research and Evaluation.
As a 5th grade teacher, I believe that research is a process to gain knowledge and information, whereas evaluation assesses the success of a program, organization, etc.
What is your educational role, and how do you differentiate between Research and Evaluation?
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I see no practical difference. However, evaluation typically identifies a single causal path from treatment to effect. Tools like random assignment, instrumental variables, regression discontinuity, and difference-in-differences are especially useful. “Research” may do the same, but often it takes a broader perspective where causal paths are entangled. Good research is often exploratory, but good evaluation always attempts to establish causality.
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I am a graduate student at Arizona State University taking a course in research and evaluation in education. In our class, we are comparing and contrasting research and evaluation. After having read our text, (Mertens, 2020) Research and Evaluation in Education and Psychology, the author discusses the differences and parallels between the two. I had previously considered the two as interchangeable terms, or at least going hand-in-hand, however now there are evident distinctions that I can identify. The two do have overlap, but to me, research seems to be more of a process of uncovering and collecting new information in order to determine the "why" of a problem, scenario, or phenomenon. Evaluation, on the other hand, presents to me as a thorough process through which already available information is compiled to identify the "how well" or worth/value of an existing program or practice.
I am curious as to others' opinions on this topic. Do research and evaluation overlap, or are they singular and distinct? How are they used together? Must they be?
We are also discussing four paradigms that frame research and evaluation. Mertens (2020) describes them as post-positivism, constructivism, transformative and pragmatic. Do you feel that one paradigm would be more useful than another in carrying out research dealing with the efficacy of teachers of gifted populations based on their understanding of those students?
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Dear Ms. Hunt!
You raised a very important issue to consider. May I argue that research is a "collective platform" for working with science while evaluation (measuring) is a toolset to advance science and education. I searched for resources to support my claim:
1) Valle, N., Brishke, J., Shenkman, E. et al. Design, Development and Evaluation of the Citizen Science Cancer Curriculum (CSCC): a Design and Development Case Study. TechTrends (2022). https://doi.org/10.1007/s11528-022-00737-6, Open access:
2) Blankenberger, B., Gehlhausen Anderson, S. & Lichtenberger, E. Improving Institutional Evaluation Methods: Comparing Three Evaluations Using PSM, Exact and Coarsened Exact Matching. Res High Educ 62, 1248–1275 (2021). https://doi.org/10.1007/s11162-021-09632-0, Open access:
3) Álex Escolà-Gascón, Josep Gallifa, How to measure soft skills in the educational context: psychometric properties of the SKILLS-in-ONE questionnaire, Studies in Educational Evaluation, Volume 74, 2022, https://doi.org/10.1016/j.stueduc.2022.101155. Available at: https://www.sciencedirect.com/science/article/abs/pii/S0191491X22000323
4) Daraio, C., Vaccari, A. How should evaluation be? Is a good evaluation of research also just? Towards the implementation of good evaluation. Scientometrics (2022). https://doi.org/10.1007/s11192-022-04329-2, Open access:
Yours sincerely, Bulcsu Szekely
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Hello everyone!
I am a graduate student at Arizona State University and we are focusing on the difference between research and evaluation. I teach Kindergarten and am working toward my Literacy Education graduate degree. In my opinion, research focuses on gaining new knowledge about a topic or purpose, while evaluation focuses on the program or purpose already used and then asking questions about it to understand its effectiveness. In your opinion, what is the major difference between research and evaluation?
As a classroom teacher, how do you think this be utilized or defined in a classroom, especially at the primary level?
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I think that the research is expansion and comprehensive as it is based on research in the depth of the issue and the problem under study with the help of previous theories and studies that can be proven or denied. I think that the evaluation is a subsequent step for the research to ensure that the required results are achieved
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I need to statistically analyse the speed-accuracy trade-off for a reaction time task.
The design of my study is: 2*2*3 (group, task difficulty, valence condition)
I want to check whether there is a speed-accuracy trade-off between the two groups under low and high task difficulty. I came across this paper but the statistical analysis given here is quite confusing to me.
Could someone tell me the stepwise process in SPSS?
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I do not recommend the approach used in the linked study. Truth be told, I cannot figure out why the authors used the statistical procedures they did, and I'm not convinced the results support the claims they're trying to make.
I suggest keeping things simple. Do two separate analyses - one with the reaction time data - and one for participant accuracy. In SPSS, you could conduct a multiple regression for the RT data. You could then conduct a binomial logistic regression for the accuracy data, coding responses as 0 = error, 1 = correct.
I presume the task difficulty manipulation is intended to create variability in participant accuracy. If participants are using a speed-accuracy trade-off strategy, you should observe the following pattern across the two tests: as accuracy decreases, response time also decreases and vice versa.
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What is the best and simplest tool (other than Excel) for making comparison charts such as line charts for algorithms comparison and evaluation purposes?
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It depends on which operating system you use on your desktop. Some suggestions I have for you are:
1 - Graph
2 - Graphmatics
3 - R Studio
This software are for building line graphs, hope I helped.
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Dear colleagues,
I’m conducting a study that is intended to identify determinants of evaluation use in evaluation systems embedded in public and non-profit sectors. I’m planning to conduct a survey on a representative sample of organizations that systematically evaluate the effects of their programs and other actions in Austria, Denmark, Ireland and the Netherlands. And here comes my request: can anyone of you, familiar with evaluation practice in these countries, suggest what types of organizations I should include in my sample? Are there any country-specific organizations active in the evaluation field that I should not omit?
It is obvious to me that in all these countries evaluation is present in central and local government (ministries, municipalities, etc.) as well as institutions funding research or development agencies, but I also suspect that there might be some country-specific, less obvious types of organisations which are important “evaluation players”.
Thanks for any hints.
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Austria is conducting such an evalutation through the AUVA. You can contact, and use my name :
DI Georg Effenberger
Austrian Workers’ Compensation Board
Head of Prevention Department
Vienna, Austria
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Through multiple empirical studies, I have collected user needs for an ICT intervention. During this study, I intend to design a prototype and then evaluate the prototype to check whether user needs are captured in the proposed design.
What is the most suitable approach? Quantitative, Qualitative or mixed?
Are we evaluating the features of the prototype or evaluate the user requirements?
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Usability testing only can compare a product with another. Higher score means better usability. But it cannot evaluate whether the proposed features in the prototype is satisfying the users.
You can ask few questions related to user satisfaction. May be as an open ended questions or a likert scale.
You also may use and correlate NET promoter score and NASA task load index with above-mentioned scales/questionnaire.
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propolis (Bee Glue) and Evaluate Its Antioxidant Activity
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Propolis can interact with ACE2 and TMPRSS2, potentially blocking or reducing SARS-CoV-2 invasion of the host cell. Propolis has also shown promise as an aid in the treatment of various comorbidities that are particularly dangerous in COVID-19 patients, including respiratory diseases, hypertension, diabetes, and cancer.
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I am now working with the project of "Evaluate the Impact of the Implementation of GDPR on the Role of the European Court". Before conceptulizing it for the discussion, I need to collect some data and have some ideas of the discussion for it. Do you have any articles or reasearches recommended about this topic?
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If you search on the European court website, what are you looking for?
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Dear colleagues, dear participatory-action research practitioners,
I would like to open the discussion on the criteria for evaluating participatory research (whether it is action-research, participatory action research, CBPR, etc.).
How do you evaluate participatory research projects that are submitted for research grants and/or publications (papers) ? Do you apply the same criteria as when you evaluate non-participatory research projects? Or have you developed ways to evaluate non-scientific dimensions such as the impact of this research on communities, the quality of connections between co-researchers? And if so, how do you proceed ?
Thank you in advance for sharing your experiences and thoughts.
Pour les collègues francophones, n'hésitez pas à répondre en français ! Quels sont les critères que vous utilisez pour évaluer des projets de recherche participative ? Utilisez-vous les critères d'évaluation scientifique que vous appliquez aux autres types de recherche ou est-ce que vous avez des critères spécifiques et si oui, lesquels ?
Baptiste GODRIE, Quebec-based social science researcher & participatory action research practitioner
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the Health Research Board in Ireland has adopted the following approach to its evaluation of grant applications
...Until recently, public reviews have been used solely to provide direct feedback to applicant teams so they could take that feedback on board, and thereby gain experience of incorporating Public and Patient Involvement (PPI) into their research proposals.
From now on, integrating the public reviews into panel decision making will be the norm for calls which undergo public review, and this step is in line with our published plans to strengthen PPI input into HRB decision-making processes.
In addition to feedback on the scientific aspects from the international peer-reviewers, the HRB receives written feedback on the quality of Patient and Public Involvement (PPI) from two public reviewers for each application ahead of the panel meeting.
All of the reviewers’ comments (both public and scientific) are passed on to the applicants, who have the opportunity to respond. The reviews and the related applicant responses are made available to the panel before they meet....
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Hello my fellow Scientists!
I'm a psychology student (Bachelor's 4th year) and I'm writing my final thesis on problematic gaming (gaming disorder) among students and it's correlation between attachment style (Bowlby theory). I was hoping to find fellow scientists who could help me by sharing (or directing me to) a questionnaire about problematic gaming and attachment style (anxious/avoidant/secure) evaluation scales.
Also how can I get in contact with the right people who have such information?
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Hello. There are a number of available scales to measure problematic gaming. I recently published a scoping review which includes a Table (Table 3) that has an overview of different scales that have been used to measure gaming disorder. These include the Game Addiction Scale, the Pathological Gaming Scale and the Internet Gaming Disorder Scale.
For attachment style, the measures will depend on the age of the people you are looking at. If this is among adults, there are a few self-report scales available including the Relationship Structures (ECR-RS) Questionnaire.
There have been a number of research articles published on the topic you want to look at. I would encourage you to go on PubMed or Google Scholar and type in "gaming disorder" and "attachment style" as keywords to get access to this literature. You can look at the measures used in these studies and decide whether you want to use the same measures or different ones.
Good luck!
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What is the Impact of drip irrigation on water use and crop production? What percent of water does drip irrigation save compared to flood irrigation? By what amount does drip irrigation increase the crop production compared to flood irrigation?
Can you please also share any relevant publication?
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Tomchilatib sug'orish orqali suv tuproqning qaysi qatlamigacha yetib boradi?
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Does anyone have any idea how to evaluate a supper capacitor with a 10Watt solar PV system?
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In order to create new procedure for performance evaluation studies, i need an ECCLS document which named "Guidelines for the Evaluation of Diagnostic Kits: Part 2: General Principles and Outline Procedures for the Evaluation of Kits for Qualitative Tests 1990, no. 1". Unfortunatelly, i could not find the document. If anyone have it, please share me. For your interest, many thanks.
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Dear Kübra Avci , you seem to be right that this paper and the entire ECCLS vanished into thin air...
I however found this listing of papers where the ECCLS was co-author/editor here on RG:
On the top-right you are being pointed to a Mr. Horobin who appearently was involved with the ECCLS at some time and has quite an active profile here on RG - maybe it could proof fruitful for you to contact him and ask who was in charge of archiving the ECCLS documents.
Good luck!
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Evaluation tool in a qualitative research in promoting values educ using different episodes
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I need to evaluate a pure content-based recommender system for documents extraction (It may also be seen as a search engine) that gets top N results based on a similarity score. I know there are some metrics like HR@k, accuracy@k, NDCG@k, CTR, etc. However, if I understand right, all those metrics require a pre-evaluation from expert coders, rating score for documents (e.g., scale from 1 to 5) or click pattern from users.
This content-based recommender systems have no user (yet) to rate/click on query results, and I can not understand how the expert coders can provide ratings for every document against every possible query.
Are there any means to evaluate such types of content-based recommender systems?
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Without human intervention (domain expert), it is not possible to calculate accuracy, precision, recall, F-1. In short, we need gold label data.
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Dear colleagues
I have a query regarding the most appropriate experimental design and statistical analysis for a research project. The project study area is located in a high altitude lagoon (Los Andes, Peru). The study subject is an endangered frog species (the Lake Junín frog).
The research question is: What is the impact of heavy metals, eutrophication and water level variation on the abundance and biomass of the Telmatobius macrostomus and T. Brachydactylu population?
After many field visits and literature research we've found out the 3 main environmental pressures on the frog population: (i) heavy metals from mining activities, (ii) eutrophication produced by untreated urban sewage discharge and (iii) water level variation to assure enough water for hydropower downstream. We have monitoring data (from secondary sources) on heavy metal concentration and some eutrophication indicators (N, P, DBO). For now we only have the resources to collect field data on water level variation, and the frog's biomass and abundance.
Currently we don't have resources to collect more data on heavy metal pollution or nutrient content in the water. Therefore, with the available data, we want to have some idea on what are the most relevant environmental pressures to:
- Know where to allocate more resources on monitoring and
- Evaluate some remediation techniques to improve the frog's habitat.
Thanks in advance for your comments.
ps. Feel free to contact me if any of you are interested in helping designing the study.
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Dear Dalia, Kindly follow the references, although I think you need more papers for comparing the contamination and pollutions, by the way , you can ask me to send other articles for your discussion part!
Anyway, hope they would be helpful:
1- Distribution and Accumulation of Heavy Metals in Surface Sediment of Lake Junín National Reserve, Peru; Available online:
and it is in research gate !
2- The heavy metal contamination of Lake Junín National Reserve, Peru: An unintended consequence of the juxtaposition of hydroelectricity and mining
3- The History of Mining in Cerro de Pasco and Heavy Metal Deposition in Lake Junin Peru ( it related in 2012 and I attached it)
4- Protected Area Profile Perú Junín National Reserve ( It has been attached)!
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I am working on EEG classification task. I segmented each hour into 30 seconds windows. I want to calculate FPR/hour. I found this formula ===> FPR/h= fp/[((fp+tn)*30)/60*60] but I didn't understood it and used my formula which is ==> FPR=fp/(fp+tn) then I divide FPR to number of hours
number of hours= ((tn+fp)*30)/60*60 then FPR/h=FPR/number of hours.
I want to be sure that my formula is true and right to use.
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I am working on a binary classification task. I want to calculate the evaluation metrics to calculate sensitivity, FPR and accuracy for each patient. I used the threshold method to calculate the metrics. I took mutliple threshold values (from 0.4 to 0.75 with step 0.05 ) to choose the best threshold. My question is can I use different threshold for each patient??
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NO. The best way to use a single specific threshold for your data analysis. Various thresholds may means that you are using only the bias to accuracy or preferred ones.
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kindly provide me with the link
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Shekhar Koirala I have searched the link you have shared, but I did not find any ground truth file of the evaluation dataset
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1. Role of Monitoring and Evaluating finances in enhancing the performance: Comparing the two and explain their usage?
Monitoring Finances
Evaluating Finances
2. What do you think should be done, procedure, or be used to be followed?
3. Which is the best way or any mentioned above can be used to ensure that monitoring and evaluating finances can help overcome?
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This article will be helpful.............
Emerging Challenges and Roles for Quantity Surveyors in the Construction Industry
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Is it the novelty of the research idea that matters or the impact factor of the journal in which the research article is published while applying for a post-doc position? Impact factors are regularly updated and keeps changing. How the impact factor truly evaluates the quality of a research article?
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The conditions for accepting a Post Doc. fellow varies across universities.
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Evaluation Metrics
RMSE - Root Mean Square Error
RMSLE - Root Mean Squared Log Error
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RMSLE metric only considers the relative error between and the Predicted and the actual value and the scale of the error is not significant. On the other hand, RMSE value Increases in magnitude if the scale of error increases. https://medium.com/analytics-vidhya/root-mean-square-log-error-rmse-vs-rmlse-935c6cc1802a
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- In general, there are types of data that interact with different types of policies, for any thematic involved.
- It is important to identify the types of data that are transversal to the public policy evaluation steps, so that they can be reused several times.
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Ana Maria Arias Castaño Gracias por tu respuesta y tu interés en la pregunta. Ciertamente considero la pregunta que mencionaste sobre el contexto del PP. Hay contextos que son transversales a cualquier política, como considerar el territorio y el componente geográfico de los datos. Esta es una forma de facilitar el acceso a los datos y hacer transparente la formulación, implementación y evaluación del PP. Es un debate interesante. Muchas gracias por su respuesta.
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Watershed development is the set of practices to impound the flowing rainwater, and thus help it percolate. But the groundwater recharge is also dependent on many other factors like the amount of rainfall, rainfall pattern, topographic slope, soil type, soil thickness, rock type etc. How do we measure the impact of watershed development on the groundwater?
Please do share publications on this topic.
Thank you.
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As pointed out by Kiprotich Kiptum, one needs to look into quantifying the declined yields. To put it more appropriately, the concretization or increase in the imperviousness of the watersheds will decrease the natural recharge rates that will impact the water tables.
So if the water tables are decreasing, it is a direct consequence of the development, (yes if development here means concretization)!
There are different methodologies for quantifying this issue, and they are discussed elaborately in literature.
I hope this has worked!
Thanks and regards
Gowhar Meraj
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I am trying to work on how variable characteristics can help to determine variable structure and pattern. I am half way into the work though.
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The 1-PL (Rasch) and 2-PL (Birnbaum) models of Item Response Theory (IRT) both imply that the items are unidimensional (i.e., that they measure a single underlying latent variable). Model misfit would indicate that there is a violation of the unidimensionality implication for either one of these models.
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I am currently working on my master thesis and have faced some problems in designing a survey. The goal is to analyze a transition from ordinary offline retailing towards physical showrooms effectuating fulfillment of products through an online shop. I use as dependent variable customer satisfaction (reaching from 1-10) and as independent variables the following ones: F= fulfillment (1/0) 1=now 0=in 3 days A=assortment (from 10 to 20 units per shop) P=price (from 25 to 25*0,7discount->17,5) Is it possible to design a survey/ experiment in a way to get the needed data for this equation?
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I am also interested to the answers of this topic.
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Dear Colleague,
Part of my Ph.D. thesis needs to be completed questionnaire, which, unfortunately, due to Covid 19, we cannot attend the company under review. For this reason, I request supply chain experts who wish to complete the questionnaire to notify me, that I will email the questionnaire to them. It would be your generosity to respond to the questionnaires and also distribute them among your colleagues, students, and networks.
Thank you in advance for your help and cooperation.
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I would like to start a discussion on which index is more reliable, H-Index or i10-Index. Both are usable, however their ways of calculation are different. There is also G-Index. I am not asking on the differences but on their reliability. Welcome to any comments.
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Good question,but both are so low for me that it does not matter.
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I'm excited to be taking on a secondment role with the University's Student Engagement, Evaluation and Research (STEER) team and am building up my reading list!
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In this paper is presented how to establish a working system for the achievement of scientific results that characterize a university.
The structuring of the research pyramids around the projects of the research groups stands out, integrating science with the graduate and undergraduate processes, with the participation of the students.
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I am training a custom dataset (RarePlane) with DeepLab V3+ using Detectron2 (open source are wroten base on Pytorch).
The custom dataset is fixed with an image size is 512x512. When I trained with 100000 interactions, I got the mIoU values (bellow).
[05/10 06:13:49] d2.evaluation.sem_seg_evaluation INFO: OrderedDict([('sem_seg', {'mIoU': 48.263697089435894, 'fwIoU': 93.17537826963293, 'IoU-a': nan, 'IoU-i': 0.0, 'IoU-r': nan, 'IoU-c': nan, 'IoU-f': nan, 'IoU-t': nan, 'mACC': 50.0, 'pACC': 96.52739417887179, 'ACC-a': nan, 'ACC-i': 0.0, 'ACC-r': nan, 'ACC-c': nan, 'ACC-f': nan, 'ACC-t': nan})]) [05/10 06:13:49] d2.engine.defaults INFO: Evaluation results for custom_dataset_test in csv format: [05/10 06:13:49] d2.evaluation.testing INFO: copypaste: Task: sem_seg [05/10 06:13:49] d2.evaluation.testing INFO: copypaste: mIoU,fwIoU,mACC,pACC [05/10 06:13:49] d2.evaluation.testing INFO: copypaste: 48.2637,93.1754,50.0000,96.5274
I'm looking for a solution to configuring the DeepLab code with detectron2 and how to increase mIoU values.
Thanks.
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ohhhh no idea man sorry
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I am conducting an evaluation of professional development using Guskey's Five Levels of Evaluation. I am trying to decide if it is an incorrect application of his model to use the same evaluation question at level 3 and level 4.
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yes, the questions in each level can be related.
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My simulation is stuck at 'evaluating n1-dvs.cmd.
Does anyone know what causes this? The simulation does not error out, but remains at this point.
i am simulating an AlInN/GaN stack. Anyone willing to review my structure file?
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welocme!
You have to return to the manual of the Sentaurus software to see the cause of the hanging of the execution of the program.
This may be the systematic path to the solution.
May be a method to get rapidly acquainted to program is the study some of its tutorials especially those related to your device.
You will learn in a practical way how do you prepare an input simulation file for your device and how to run the simulation and how do you postprocess the results.
For the manual please look at the link: Sentaurus™ Device User Guide - ResearchGate
Best wishes
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What is the best superimposition software to the comparison of two similar virtual 3D objects?
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I'm working on generative models for medical image synthesis, specifically GANs for CT image synthesis. What are the evaluation metrics best suited for evaluating a proposed model?
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You can consider using the Fréchet inception distance (FID) which is a metric that could assess the quality of synthesized images created by GAN.
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Please help me to prove the code to solve the following problem;
Problem: "Semantic segmentation of humans and vehicles in images".
Following are the given information related to solve this problem;
Experimental study:
 using a learning machine model: SVM, KNN, or another model
 Using a deep learning model :
 either Semi-dl: resNet, VGg, inception (Google net) or others
 full DL site: Yolo, unet, CNN family (CNN, RCNN, faster RCNN), or others
 Evaluation of the two models in the learning phase
 Evaluation of both models with test data
 Exploration & descriptions & analysis of the results obtained (confusion matrix, specificity, accuracy, FNR)
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Thanks to all
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Why Green-Gauss Node Based Gradient Evaluation is preferred over default Green-Gauss cell Based in ANSYS FLUENT?
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this method is more accurate on meshes with higher mesh skewnesses. In most cases you should be using the Least-Squares Cell based methods however, which should be faster (and more accurate) than the Green-Gauss Node Based Gradient method, at least on static meshes, in the most cases.
If you have a dynamic mesh or "hanging nodes" in your mesh using the Green-Gauss Node Based Gradient method may be beneficial over the Least-Squared methods, at least of what I know of...
But Omer A. Alawi is right, if you do not know anything about these methods, search for the video on yt and draw your own conclusions.
Best regards
Christian
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It is natural that employees can have emotional effort as well as physical and cognitive effort. Emotional labor—the effort required to manage one's feelings or emotions at work—plays a significant part in many occupations.
Employees’ emotional efforts that are in harmony with business ethics can be defined as emotional labor. Evaluating emotional labor based on business ethics seeks to enable managers to reduce the negative consequences of emotional labor while preserving the positive ones.
Surface acting does not involve real feelings. It depends on fake emotional presentations. Therefore, surface acting can be evaluated as unethical emotional efforts. As a result, these fake emotional presentations can not be accepted as emotional labor.
Öngöre's findings (2019, 2020) showed that natural emotions do not cause emotional exhaustion (burnout), while surface acting causes emotional exhaustion. Meanwhile, natural feelings causes vigor and dedication (work engagement).
References:
Öngöre, Ö. (2016). A theoretical study about the place and value of emotional labor in working life, Atatürk University Journal of Economics & Administrative Sciences, 30(5), 1161-1177.
Öngöre, Ö. (2019). Determining the Effect of Emotional Labor on Work Engagement: Service-Sector Employees in Private Enterprises. Turkish Journal of Business Ethics, 12(1), 126-134.
Öngöre, Ö. (2020). Evaluating emotional labor: A new approach. Global Business and Organizational Excellence, 39, (4):35–44.
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Burçak Hanım yolun başında genç bir araştırmacı olduğunuzu varsayıyorum. Size tavsiyem bu tartışma başlığının ekindeki makalelerimi okumanız. Teşekkürler.
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I am looking for advice concerning a (supposedly) known practical issue : article overloads. While doing my PhD I was convinced that everything who went through publication was worth reading and understanding. My opinion as evolved since then for very practical consideration : lack of time to read biblio and absolute necessity to "pre-screen" something before deciding if it's worth reading or not.
Concerning scientific paper, the prescreening can be tricky. Since the format is very standardized as well as the wording (nothings sounds more like a paper than a paper), I often end up reading half a dozen page on a paper, annotates parts, spend time... before deciding I shouldn't spend time on it.
Do you have some "tricks" to share in order to lower that waste of time? While these "tricks" might be completely non-scientific of course, I still would enjoy them
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If you are reading the prior work just for your literature review, you don't have to meticulously read them as if you are reviewing them as a referee. However, if you identify some errors or shortcomings, take a note of them, perhaps you might end up with another paper idea from them. You just have to identify what is different compared to your paper and how your paper is an improvement or a different but important paper looking from another aspect, etc. If it is highly related to your paper, and you need to be very specific to convince the readers that your contribution is significant, then you should read it very carefully. If you need to get a general idea about the area, for a potential research, then you will need to read the most important (highly cited) and early work on that subject very carefully. You also need to read the most recent work, to be up-to-date on the subject. Your reading of the earliest, the most influential and the latest papers on the subject will lead to more papers to read, to guide your literature review and to improve your understanding of the state of the art in the area.
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I want Researchers from Educational Measurement and Evaluation, relating to teaching, learning , academic performance and test validation
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yes, you can do it
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I just completed my doctorate, I live in Massachusetts, and I have 2 years of experience with evaluation in the social sciences. If I were to create an evaluation plan for an organization, how much should I charge per hour of work? My acquaintance has recently started a business and neither of us know how much to charge for evaluation. If possible, please leave a rough numerical range... even if it is just a guess. Thank you so much in advance!
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Dear Alex,
My point was that such a question could not really be answered precisely. Ultimately, it is up to a negotiation between the consultant and the contractor. I have done very little consulting in the health or business world, so I don't really have an answer for you. However, I suggest this for people starting out. That is to ask the contractor is they have a standard range they pay. After one gains some experience, they learn a reasonable range to ask.
Good luck,
Jim McLean
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Hello Everyone,
I have a questionnaire of a 3-point Likert scale for an overall evaluation for a service, and several detailed attributes evaluation of that service. For example:
Overall Evaluation (1-3), then
Cleanliness (1-3)
Comfort (1-3)
Privacy (1-3)
..etc
I am looking for a way to find what are the most important variables (attributes) that have the highest impact on overall evaluation.
Is ordinary regression helping?
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Ordinal logistic regression (ordinal regression) is applicable when one aims to predict an ordinal dependent variable given one or more independent variables. Independent variable(s) may be categorical or continuous. Data used should meet the following assumptions:
(1). The dependent variable should be measured at the ordinal level;
(2). One or more independent variables should be continuous, ordinal or categorical; and
(3). No multicollinearity (situation where two or more independent variables are highly correlated with each other).
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There are the following well-known ontology evaluation methods of computational ontology
1. Evaluation by Human
2. Evaluation using ontology-based Application
3. Data-driven evaluation
4. The Gold Standard Evaluation
We designed and developed a domain ontology and implemented it in OWL semantic language. How to evaluate it?
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Dear Abdul Sattar
You may read the article below, which I think can help you . Please, if still interested, send me an email by RG, since it is in private mode due to copyright.
Sincerely,
Luis
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How do you measure the outcomes of general education (up to 12th grade) and higher education (college and above) in a given country? what are some indicators you would suggest I use?
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A typical approach to the measurement of outcome is to ask students to assess their learning outcomes on a range of variables which can often be subsumed under different dimensions (e.g. knowledge, general competence and skills). Such self-reported outcomes are often aggregated to indicate the quality of programmes.
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Have been looking for the following article: Review of Experimental Techniques for Evaluating Unsaturated Shear Strength of Soil. In book: Advances in Civil Engineering and Infrastructural Development, Select Proceedings of ICRACEID 2019. DOI: 10.1007/978-981-15-6463-5_57. Is there anyone who will be able to provide it?
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Thank very much for your kind assistance.
Best regards
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How do you measure the outcomes of general education (up to 12th grade) and higher education (college and above) in a given country? what are some indicators you would suggest I use?
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In the USA, the SAT scores are a poor indicator to measure general education. Learners can take classes, and use short-term memory to memorize patterns or answers. So the learner aces the test but little else occurs in regards to education. To gain entrance into an Ivy League university, the learners do not ace any test whatsoever at all. Instead, the "wealthy" family pays for the learner to be admitted to Harvard or Princeton. I am not joking.
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I am doing text mining on the performance on research for development interventions in low income countries. I need some standard dictionaries and typologies to map the content of the paper in a standardized way. Can you the international standards you are aware of? Thanks in advance.
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applied, unapplied, Economically feasible, Not economically feasible,
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Topic
Influence of Sino-Beninese Cooperation on Structural Adjustment in Benin: The Case of textile industry
PROBLEMATIC
Cooperation is the situation in which two or more nations interact, exchange and build a common implementation that benefits them. The cooperation between China and Benin begun far beyond 1972 where diplomaticrelation was re-established. Since then, China has become an important development partner of Benin. The distance between the two countries and the language barrierdid not hamper the cooperation and resulted to couple of achievements, especially to Benin.For example, in the areas of government assistance, agriculture and fisheries, industry, Public Works, Public Health, energy, telecommunications, trade and human resources, highlights illustrate the excellent relationship between the two countries.
Furthermore, in development perspective, His Excellence Jingtao Peng said that China's cooperation includes five priorities that are, policy coordination, infrastructure interconnection which is the priority area of " Belt and Road ", trade facilitation, financial integration and cooperation of peoples with emphasis on SITEX-Société textile du Benin.Since 1987, the cooperation with target on Sitex has yielded mere production and marketing of greige fabric 100%cotton. According to Josaphat 2018, it annually imported 15 million to 20 million unbleached meters from the outside. Unfortunately, weakened by its internal underperformance, the company has succumbed to the crisis of the textile sector as the COTEB (textile complex of Benin) another purely Beninese textile company.
However, literature reveals that more need to be done under the textile fabric and derived product in order to boost the economy of African country having Cotton as state product as in Benin.Indeed, it is estimated that about 90% of the fibre is exported, with only 10% being processed into yarns and then into textiles by local industries, which is partly due to the demand for foreign exchange from parastatal marketing agencies (ICAC, 2015).By processing and exporting finished products instead of fibre, African countries would be less penalized by subsidies to American producers and Africa would industrialize.
Therefore, it is worth to assess the result of the cooperation and inform decision makers onthe impact of the long-life cooperation between Benin and China. In order words, this research aims at investigating on the influence that the partnership with China and Benin could have through its textile industry as we address the following main research question: Can cooperation between China and Benin revive Benin's textile industry?
RESEARCH OBJECTIVE
The main objective of this research is to understand why Beninese textile companies are not viable to the point where almost all cotton production is nowadays,transforms abroad. The study also intends to analyse the influence and prospects of a Sino-Beninese cooperation for the development of the textile industry.
Specifically, the research will :
§ Evaluate the influence of Benin's Sino cooperation on Benin's economic development and, above all, its textile industry
§ Evaluate the productive capacities of Benin's textile industries
§ Analyse the internal and external factors that affect the performance of textile mills
§ Develop a strategic plan to promote and enhance local processing plants with Chinese expertise
§ Suggest the clauses of a new partnership that will benefit both Benin and the Chinese side for the processing of Benin cotton
Ultimately, the study could contribute to understanding the optimization of local processing, improving the management and performance of existing enterprises as well as developing the added value of cotton through local processing of the product (into by-products).
RESEARCH HYPOTHESES
In the quest to responding to the research question, the following assumptionsare formulated:
H1) The new cooperation between China and Benin has a positive impact on Benin's textile industry
H2) The productivity of processing raw cotton into fibre and other derived products is very low compared to highly industrialized countries such as China.(Looks not good written)
H3) The cost-income structure (inputs-outputs); the quality of industrial equipment (machinery); the qualification of personnel; logistics; lead time are some of the factors affecting the performance of the textile industries in Benin..(Looks not good written)
H4) Management plans for the cotton industry have a negative impact on the processing of raw cotton into finished products that are competitive on the international market.
H5) The clauses of a new partnership are very beneficial to Benin than to the Chinese side for the processing of Benin cotton
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Zhao, H., & Lin, B. (2020). Impact of Foreign Trade on energy efficiency in China’s textile industry. Journal of Cleaner Production, 245, 118878.
Babb, S. (2005). The social consequences of structural adjustment: recent evidence and current debates. Annu. Rev. Sociol., 31, 199-222.
Mohan, G., & Lampert, B. (2013). Negotiating china: reinserting African agency into china–Africa relations. African Affairs, 112(446), 92-110.
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Evaluate integral.
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this is nice question this question can be slove with the help of Laplace transfrom
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Hello,
I am looking to evaluate the quality of a land use plan in my country. However I am limited by availability of criteria to use. Do you know of literature I can review or advice on standards used in the planning profession when conducting a plan quality evaluation?
Your response will be much appreciated.
Regards, Malakia
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Your question helped me too. Thanks for asking here.
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How many of you have had a look on https://arxiv.org/pdf/1810.01605.pdf where Prof. J.E. Hirsch suggests new, improved "h-indexes" "to quantify an individual’s scientific leadership"? Formal evaluators just love the original h-index, it's easily obtained from WoS, GS, Scopus etc data bases. How much can or should this (or some improved parameter) be relayed on evaluating researchers success, contribution and impact?
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First, we could rely on, but as time passes the intelligent human being finds biases for every issue as well as the vaccine for the terrifying Coronavirus.The h-indexes of those who are passed away long ago is definitely reliable. Also the true h-index is provided from noble research articles or findings, not the books or the review papers that are originated from the results of others, findings.
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Peer assessment helps students to be more objective about their own learning and it can assist learning, it is argued. Its worth to student evaluation would perhaps be questionable too.
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Peer assessment has been shown to advance learning, for example, by improving one’s work, but the variance of learning benefits within or between studies has not been explained. The purpose of this case study was to examine what kinds of pathways students have through peer assessment and to study which factors affect them when peer assessment is implemented in the early stage of physics studies in the context of conducting and reporting inquiry. Data sources used include field notes, audio recordings of lessons, student lab reports, written peer feedback, and student interviews. We examined peer assessment from the perspective of individual students and found 3 profiles of peer assessment: (1) students that improved their lab report after peer assessment and expressed other benefits, (2) students that did not improve their lab report but expressed other benefits, and (3) students that did not experience any benefits. Three factors were found to explain these differences in students’ pathways: (1) students’ engagement in conducting and reporting inquiry, (2) the quality of received feedback, and (3) students’ understanding of formative assessment. Most students experienced some benefits of peer assessment, even if they did not put effort into their own work or receive constructive feedback. Nevertheless, in this case study, both improving one’s work and experiencing other benefits of peer assessment required sufficient accomplishment of all 3 factors.
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I know there are plenty evaluate methods can be used to evaluate the clustering result for a single data set, I am trying to apply the same clustering technique to two different data sets and then compare the similarity of the resulting clusters.
for example I want to compare the result of a same clustering algorithms on two consecutive time intervals with different data.
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Sara Mirzaie: I suggested one way in my second answer above. I'd be happy to discuss further via email or a direct message here :-)
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Evaluating training design is similar to evaluating trainees reaction?
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In fact the idea is evaluation. Though the basic idea of evaluation is same, there will be differences. For example evaluating a chair quality and the perception of the one who uses chair will be different yet the basic idea of evaluation is same.
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Hello everyone,
In case of balanced classes, what is the best metric to evaluate a supervised binary classifier that predicts if a tweet will be relevant or not to a user: MCC (Matthews correlation coefficient) or F1-Score (F-Measure)?
Thanks.
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It depends on problem domain. There exists several off-the-shelf metrics, e.g. accuracy, precision, recall and so on. Each of these metrics indicates different aspects. So, the best metric cannot be generalized. It depends what the point of interest is based on problem domain. However, the mostly used metric is the accuracy for evaluating a supervised binary classifier with balanced classes.
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Evaluation of vulnerability of school children below 10 years being investigated.
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Abstract and CV submission deadline – June 30th, 2020
Call details
The John Molson School of Business at Concordia University kindly invites contributions to the forthcoming edited book Beyond the 2ºC - Business and Policy Trajectories to Climate Change Adaptation to be published by Palgrave Macmillan and being considered for the “Palgrave Studies in Sustainable Business: In Association with Future Earth” book series.
ABOUT THE BOOK
Climate change mitigation, understood as an approach to reduce human-induced emissions, has taken centre stage in climate action debates and efforts in the last decades. Currently published reports and studies present scenarios under which we can limit the global temperature rise to a 2°C threshold. However, to stay within the 2°C threshold, we need to move towards net-negative global emissions. This would require mobilization on a global scale and improvements in our approaches to mitigating global warming. After passing the symbolic 400 parts per million (PPM) threshold of carbon dioxide equivalents (CO2-eq) in the atmosphere in 2016, recent studies have highlighted that the current emission trajectory can easily lead to concentrations of up to 1,000 PPM of CO2-eq – leading to an average global warming of up to 5.4°C by the end of this century.
While many governments, businesses and researchers like to believe that a mitigation-focused approach can keep the 2°C threshold within reach, this edited book intends to investigate the business and policy adaptation trajectories beyond what are currently understood to be some of the major tipping points in the climate system. In these scenarios, the planet will be on an accelerated path towards deforestation, biodiversity loss, erosion of inhabited and uninhabited coastal areas, and the possible disappearance of entire island states. These events will be coupled with the possible proliferation of disease, human migration, and increased conflicts over resources. This calls for academics, practitioners, and policymakers to shift their attention away from the almost exclusive focus on climate change mitigation, to also consider adaptation plans.
Beyond the 2ºC - Business and Policy Trajectories to Climate Change Adaptation is an edited collection that will review and critically analyze new and innovative business and policy approaches to climate change adaptation across different economic sectors and for different locations. The edited collection will aim to ignite an academic discussion regarding the necessary, and potentially urgent, adaption strategies that could address the risks induced by the fast-changing climate. The contributions should demonstrate how we can adapt to a world where fresh water is scarce, where extreme weather events are a daily reality, where global sea levels are up to 2.4 m higher than today, and where flooding and wildfires are no longer discrete events. The collection plans to evaluate the readiness of our businesses and policies to adapting to this “new” world and to explore strategies that move beyond the current incremental approaches.
CALL FOR CONTRIBUTIONS
Beyond the 2ºC - Business and Policy Trajectories to Climate Change Adaptation aims to explore and propose business and policy solutions for climate-induced economic, technical, and societal challenges.
The editors are accepting contributions by experts in both the academic and practitioner communities in business and policy, as well as related fields such as economics, management, development studies, finance, and entrepreneurship. The editors are inviting contributions that:
· Shed new light on our understanding of climate-related vulnerabilities and risks
· Explore innovative risk management procedures
· Present new and emerging processes for internalizing adaptation in existing business and policy approaches
· Identify new barriers to large scale and/or local climate change adaptation
· Introduce methodologies for mapping and understanding synergies and trade-offs in adaptation
· Investigate approaches to overcoming conflicts in business and policy adaptation trajectories
The editors are encouraging contributions that move beyond the current disciplinary divides and present novel interdisciplinary approaches, which use scenario building methodologies in their investigations and study the social, economic, environmental, and cultural dimensions of the complex adaptation trajectories. Moreover, the editors will also be accepting chapters that incorporate new concepts or tools beyond the academic fields of business administration and political science. These fields will include the natural and social sciences, which make connections to the business and policy. The editors also encourage contributions that move beyond carbon emissions to focus on emerging challenges and themes regarding adaptation, which includes health, wellbeing, air quality, waste, and biodiversity. In addition, chapters that use case studies or comparative studies (between different solutions, applications in different industries, or variations between regions) are strongly encouraged. Finally, considering the global nature of climate change and its multi-scale consequences, the editors invite authors to critically consider the scalar relevance – local, regional, national, and supranational levels – of their contributions.
The submissions will be reviewed with an open mind and with a particular focus on the relevance of the chapter with respect to adapting to climate change and its consequences beyond the 2ºC threshold. The edited book will serve as an academic reference for senior undergraduate, graduate, and post-graduate scholars in the fields of business, public affairs, social science, environmental studies, and law across the globe. It will also function as a practical guide and a reference for emerging best practices on the topic of climate change adaptation for industry and business leaders, regulators, and policymakers around the world. Although the book can be used as a reference book in academic courses, it will not be specifically organized as a textbook.
POTENTIAL TOPICS FOR CHAPTERS
1. CLIMATE CHANGE HAZARDS AND THEIR MANAGEMENT
a. Understanding the hazards and their management
b. Technological hazards
c. Political hazards
d. Natural hazards (cyclones, floods, storms, floods, droughts)
e. Socio-economic risks
f. Human health risks
g. Planetary health and biodiversity risks
h. Geoengineering and climate management
i. Greenhouse gas management
ii. Solar radiation management
2. THE FUTURE OF FOSSIL FUELS AND EMISSIONS
a. Fossil fuel subsidies
b. Carbon pricing/carbon taxation
c. Biofuel and other alternative fuels
d. Renewable energy (wind, solar, geothermal)
e. The future of nuclear power (challenges and opportunities)
f. Battery electric vehicles (BEVs)
g. Hydrogen fuels
3. ADAPTING CITIES, URBAN SETTLEMENTS, AND CHANGES TO HUMAN BEHAVIOUR
a. Urban planning, urban design, and cities beyond the 2ºC
b. Waterfront settlements, island states, and other high-risk human settlements
c. Buildings and construction (design, materials, codes/standards/certifications, retrofitting)
d. Local modes of transportation (cars and other private transport, public transit, collective passenger transport, human-powered transport, etc.)
e. Intra-continental travel (rail, advanced trains and emerging technologies)
f. Inter-continental travel (aviation fuel, turbofan/turboprop engines, emissions and contrails, emerging technologies, etc.)
g. Global product transport and logistics
4. ADAPTING THE PRODUCTION AND CONSUMPTION PATTERNS
a. Agriculture, soil, and forests
i. Animal and marine farming
ii. Agriculture, agroforestry, reforestation
iii. Soil and its rehabilitation
b. Demand-side management
i. Incentive and financing programs
ii. Change and development in consumption patterns
iii. Consumer behaviour beyond a 2ºC warmer climate
c. Supply-side management
i. Change and development in production patterns
ii. Recycling, upcycling, reuse, and regeneration
iii. Closed-loop production models
iv. Living and biotic natural resources
v. Non-living natural resources (metals, minerals, and stone)
vi. Renewability of resources
d. New and emerging modes of production and consumption
5. FINANCING GLOBAL CLIMATE ADAPTATION
a. Microfinance (micro-credit, micro-insurance, risk, etc.)
b. Philanthropy and venture capital
c. ESG investment (trends, renewable energy investment, partnerships, water, etc.)
d. Climate finance (private climate finance, green funds, adaptation funds, the low carbon market, divestment, etc.)
e. Evaluating and managing the financial risks of adaptation
f. Natural capital accounting (efforts, innovations, and effects)
g. Financial policies
6. LIMITATION AND THE FUTURE OF CLIMATE ADAPTATION
a. The limits to climate change mitigation
b. Political and policy limits
c. Capital limits
d. Technological limits
e. Societal and cultural limits
IMPORTANT DATES
· Abstract and CV submission deadline – June 30th, 2020
· Selection of abstracts and notification to successful contributors – July 31st, 2020
· Full chapter submission – November 30th, 2020
· Revised chapter submission – February 28th, 2021
GUIDELINES FOR CONTRIBUTORS
Submissions should be written in English using a non-technical writing style. The contributions may include diagrams/illustrations in order to present data, or photographs/figures (all in black & white) to better illustrate the topic of discussion. Submitted chapters should be original and exclusively prepared for the present book. No part of the article should be published elsewhere. Chapters must not exceed 7,000 words (including all references, appendices, biographies, etc.), must use 1.5-line spacing and 12 pt. Times New Roman font, and must use the APA 7th edition reference style.
Researchers and practitioners are invited to submit abstracts of no more than 500 words, a bibliography for their proposed chapter, and a CV. Abstract submissions are expected by June 30th, 2020. Submissions should be sent via email to climatechange.adaptation@concordia.ca
Authors will be notified about the status of their proposals and will be sent complete chapter guidelines. Full chapters are expected to be submitted by November 30th, 2020.
Please note there are no submission or acceptance fees for the manuscripts.
ABOUT THE EDITORS
Thomas Walker[1]
Dr. Walker holds an MBA and PhD degree in Finance from Washington State University. Prior to his academic career, he worked for several years in the German consulting and industrial sector at firms such as Mercedes Benz, Utility Consultants International, Lahmeyer International, Telenet, and KPMG Peat Marwick. He has taught as a visiting professor at the University of Mannheim, the University of Bamberg, the European Business School, and the WHU – Otto Beisheim School of Management. His research interests are in sustainability & climate change, corporate governance, securities regulation and litigation, and insider trading and he has published over sixty articles and book chapters in these areas. He is the lead-editor of five books on sustainable financial systems, sustainable real estate, sustainable aviation, emerging risk management, and environmental policy. Dr. Walker has held numerous administrative and research positions during his career. For instance, he served as the Laurentian Bank Professor in Integrated Risk Management (2010-2015), Chair of the Finance Department (2011-2014), Director/Co-director of the David O’Brien Centre for Sustainable Enterprise (2015-2017), and as Associate Dean, Research and Research Programs (2016-2017) at Concordia University. In addition, he has been an active member of various advisory boards and steering committees including, among others, the human resources group of Finance Montréal, the steering committee of the Montreal chapter of the Professional Risk Managers’ International Association (PRMIA), the academic advisory board of the MMI/Morningstar Sustainable Investing Initiative, and the advisory board for Palgrave Macmillan’s Future Earth book series on sustainability.
Stefan Wendt[2]
Dr. Wendt is an Associate Professor and Director of the Graduate Programs in Business at Reykjavik University’s Department of Business Administration. From March 2005 until March 2015 he was Research and Teaching Assistant at the Department of Finance at Bamberg University, Germany, where he received his doctoral degree in 2010. He has taught as a visiting lecturer at École Supérieure de Commerce Montpellier, France, and Baden-Württemberg Cooperative State University (DHBW), Mosbach, Germany. His fields of research include corporate finance and governance, risk management, financial markets and financial intermediation, small and medium-sized enterprises, and behavioural finance.
Sherif Goubran[3]
Sherif is a PhD. candidate in the Individualized Program (INDI) at Concordia University, a Vanier Scholar, and a Concordia Public Scholar. He is conducting interdisciplinary research within the fields of design, architecture, building engineering and real-estate finance. His PhD research investigates the alignment between sustainable building practices and Sustainable Development Goals (SDGs). His research focus includes building sustainability and sustainability assessment, sustainability in architectural design and human approaches in design. Sherif completed a MASc in building engineering in 2016 with a focus on energy efficiency in commercial buildings. Before that, he completed a BSc in Architecture at the American University in Cairo (AUC-Egypt). Today, he is actively engaged in several research laboratories, centers, and groups where he teaches and conducts research in design, engineering, architecture, and business. He is also involved in several sustainability committees and projects at Concordia on the student as well as the administrative levels.
Tyler Schwartz[4]
Tyler is currently a research and book publication assistant in the Department of Finance at Concordia University. He recently completed his undergraduate degree at the John Molson School of Business in which he received an Honours in Finance. As part of his undergraduate degree, he completed a thesis project in which he wrote a paper focusing on the relationship between data breaches, security prices, and crisis communication. He was also presented with the CUSRA scholarship in 2017, which is awarded to undergraduate students who have an interest in pursuing research activities. His research interests include sustainable finance, machine learning, data breaches, and cognitive science.
[1] Concordia University: thomas.walker@concordia.ca
[2] Reykjavik University: stefanwendt@ru.is
[3] Concordia University: sherif.goubran@mail.concordia.ca
[4] Concordia University: tyler.schwartz@mail.concordia.ca
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Bartlett H, Westcott L, Hind P, Taylor H (1998) An Evaluation of Pre-Registration Nursing Education: A Literature Review and Comparative Study of Graduate Outcomes. Oxford Centre for Health Care Research and Development, Oxford Brookes University, Oxford.
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No. However, we begin by: where did you get the reference from? then, definitely it must be somewhere if you tirelessly search for it.
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Hey everybody :)
I am writing my masterthesis about the influence of climate of Innovation on the innovativeness of Ideas.
The study was conducted in a company and employees could post their ideas on an online-plattform. There were two "Idea-Boxes" to sort the ideas. 1. New Working Processes and 2. New Products and Services.
I have a scale to measure product innovativeness based on Schultz et al., 2013. "Measuring New Product Portfolio Innovativeness: How Differences in Scale Width and Evaluator Perspectives
Affect its Relationship with Performance"
But with this scale it is hard to measure the innovativeness of working procesess f.e. one idea is to establish an "Innovation Team" or another idea is the use a "Cloud-saving" System. So basically in this box is every idea, which can improve the processes of teams or the whole organization.
What I need is a scale to externally measure innovativeness of working processes. So experts have to rate the ideas.
I searched for this kind of scale, but did not find any.
Thanks in advance.
Greetings
Christian
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Evaluation metric to assess superpixel based algorithms
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Educ 6782 Assessment and Evaluation course 
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assist with determining an individual's academic strengths and weaknesses, diagnosing ... new tests in the WJ IV ACH; however, it no longer includes tests of oral ... to each test—including suggested starting points and basal/ceiling rules—are 
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Hi everyone, I want to learn as much as possible about survey methodology for evaluation purposes. I'm particularly interested in research around validity and reliability of: question types (format, types, what's best for what purpose) likert-type scales (how many items, what labels to use, etc), and how to design questionnaires to avoid or minimize biases (e.g. primacy, recency effects, leniency effects, halo effects etc). Basically, I'm trying to answer a question like: "Does it matter how you ask the questions when you are evaluating others?".
Could anyone recommend some journals or meta-analyses or authors or specific search terms that could help me learn more?
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See also:
1. DeVellis, R. F. (2016). Scale development: Theory and applications (Vol. 26). Sage publications.
2. John, G. and Reve, T. (1982), The reliability and validity of key informant data from dyadic relationships in marketing channels, Journal of Marketing Research, 19 (4), 517-524.
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Let's suppose we want to compare for a given problem several supervised learning algorithms, in terms of accuracy and speed.
If we don't have a lot of data, is it acceptable to duplicate instances to assess the speed performance?
I know it's not recommended when assessing the accuracy, but what about the speed?
Thanks in advance.
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After some reasoning, research and experiments, I come back to answer my own question so that others can benefit from it. As mentioned in the question, I asked if duplicate data can be used to assess the speed only, not the accuracy. I have come to this conclusion:
Duplicate data is not appropriate to assess the speed and scalability performance of supervised learning algorithms. Let us take a simple example of a decision tree, the model c