User:PanosKratimenos/sandbox/BASC001/2020-21/Thursday2-3/Evidence

Psychology
Psychology is concerned with the phenomenon of the mind and the unobservable mechanisms which produce observable effects that can be studied through behaviour or speech; for example, relating subconscious patterns of thought to the emotions that are experienced by an individual. Psychology predominantly understands emotion as a state of mind from a phenomenological perspective concerned with the perception, interpretation and meaning of an experience to an individual. This approach utilises the ability of qualitative data to capture an individual's experience in as much depth as possible to accurately reflect their internal state. This is done through methods such as unstructured interviews using open-ended questions to allow the individual to elaborate in detail on their personal experience and interpretation. Application of unstructured interviews can be seen in therapy and counselling; the patient is given the freedom to explore and explain how they feel, to allow the psychologist to deduce underlying patterns of thought correlating with the emotions contributing to their overall experience.

Psychology: Qualitative and Quantitative Evidence
In Psychology, both qualitative and quantitative methods of providing evidence can be used. Quantitative evidence refers to evidence where the data obtained is in a numerical form, while qualitative evidence is data that is not in the form of numbers, instead relating to concepts such as emotional states or experiences, that can later be quantified if needed. Qualitative research is primarily carried out in the participants’ natural setting. Examples of qualitative research methods in psychology include case-studies, unstructured interviews and focus groups. Qualitative data can consist of ethnographic text, audio recordings, photographs and more. Quantitative data on the other hand, is usually obtained through experiments or questionnaires to which statistical analysis is later carried out on.

Neuroscience
Contrary to psychology, neuroscience focuses on recording measurable and quantifiable phenomena within the brain to make sense of an experience, such as emotion, through measuring hormone levels, neurotransmitter release and blood-oxygen levels. Functional Magnetic Resonance Imaging (fMRI) uses blood-oxygen level dependent (BOLD) imaging, enabling the neural underpinnings of emotion to be traced in the brain; for example, the amygdala is seen to undergo activation during fear responses, determined by an increase in blood flow and oxygen level. Emotion is also studied on a more macro-scale through neurotransmitters and communication between neurons by mapping neurotransmitter networks in the brain and measuring neurochemical changes in Mass Spectrometry Imaging (MSI).

Reverse Inference
Reverse inference is the practice of inferring a psychological state from neural activity, and is one of the most significant issues within neuroimaging. Neurons have multiple functions and are involved in various circuits for different purposes, therefore psychological states cannot be deduced from neural activity, as the brain does not operate in such a categoric manner. Just because activation of a certain brain region has previously been correlated with a certain cognitive function in a given situation, it does not mean that whenever the same activation is observed, that specific cognitive function is being carried out. This demonstrates the importance of integrating psychological and neuroscientific methods when studying cognitive functions such as emotion, to accurately correlate neural activity with a psychological state.

Forward Inference
Psychology and neuroscience are both necessary to understand emotion through how the perceived experience and interpretation relates to neural mechanisms. A way to do this is through forward inference: inferring what brain activity means through observing a cognitive function at the same time. For example, having a participant explain how they are feeling and what emotions they are experiencing, then observing which regions of the brain are activated.

Issues
It is clear that psychology and neuroscience generally employ different methods when researching emotion; psychology predominantly produces qualitative data, while neuroscience produces more quantitative data. When conducting interdisciplinary research, problems may be encountered as a result of these different research methods, as it may be hard to relate qualitative to quantitative data to deduce correlations. The more in-depth the account of the individual's experience is, the harder it is to single out an emotion to be correlated with the observed brain activity. Furthermore, simplifying, categorising and quantifying qualitative data from psychology so it can be more easily correlated with neuroscientific evidence may defeat the point of having qualitative data, as the meanings and experience of the individual are reduced to numbers and may not accurately represent their internal state.

Introduction
Forensic Science is the study of traces that are left behind during an activity under investigation, using scientific techniques. The results obtained by the analysis of these traces can then constitute as evidence in litigious civil or criminal cases, allowing for the exoneration or conviction of potential suspects. One method of obtaining Quantitative evidence is through DNA analysis. DNA analysis involves 6 main steps.

Methods
Step 1 : The trace is detected at the crime scene, followed by the safe collection and storage of this trace to avoid contamination. Contamination being defined as other materials that are also present in the sample collected, that could pose potential threats to the case as they may lead to the misinterpretation of the results.

Step 2 : DNA extraction and purification takes place. During this, DNA is extracted out of the cells’ nucleus, through processes such as Phenol-Chloroform extraction. This specific process uses enzymes, sodium dodecylsulfate and proteinase K, to digest non- nucleic acids present in the trace, leaving behind the DNA itself however, this isn’t the only commonly used process of DNA extraction.

Step 3 : The amount of DNA present in the trace is measured through quantitation/quantification, now commonly carried out through real time PCR.

Step 4 : DNA separation ensues, ensuring isolation of the amplified DNA.

Step 5 : DNA analysis is carried out followed by a comparison of this DNA trace to an existing DNA database. One of the main methods of DNA separation is through STR Typing, where specific gene loci are targeted for analysis (13 loci) which allows us to understand if two traces originated from the same person.

Step 6 : Quality control of the sample.

While DNA analysis is sometimes believed to easily solve problems of identification in the court of law, this is not always the case. It is common for the DNA collected to only be a partial trace, where a specific locus is missing an allele or a peak on the electropherogram falls below a target threshold. Furthermore, the DNA collected may be exceptionally low in quantity, could be contaminated, or may generally be an older trace consisting of fewer DNA molecules. All of these are factors that need to be taken into consideration when analysing DNA evidence. Because of the many levels of uncertainty that are present in DNA analysis, there have been many instances of wrongful criminal convictions based upon previously thought to be ‘accurate’ DNA evidence. An example of this can be witnessed with the Amanda Knox case.

Interdisciplinary approach
Due to all the factors that need to be taken into consideration, it is easy to see why, interdisciplinary methods are often employed from the fields of biology, chemistry, forensic science, computer science and statistics before a conclusion can be reached. The person interpreting the results must have a good foundation of knowledge in biology and chemistry, to understand what is represented on the electropherogram. Additionally, DNA analysis can also be statistical in nature as well as, the analyst must have a basic understanding of how to operate the machines and software required for the interpretation of the electropherogram. Lastly, and most importantly, the analyst must understand how to word their results according to forensic guidelines. The complex process of the interpretation of evidence in forensic science further conveys the need for interdisciplinarity in this field.

Evidence for Love: The quantitative approach applied by Biology, Chemistry and Mathematics
Love is a worldwide concept that humans have been familiar with all throughout history. There are many different forms of love (romantic, compassionate, familial, and purely liking) and while humans demonstrate a craving to experience this emotion, an understanding as to why and how this feeling arises, is limited. A range of disciplines, from Philosophy to Chemistry, have tried to explain what “Love” actually is, using both quantitative and qualitative research to provide evidence. However, it remains unclear which methodologies are most appropriate for this study.

Biology
Scientific theories suggest that “Lust”, often the starting point for passionate love, is a sensation that embodies humans' intrinsic need to reproduce. From an evolutionary standpoint, it is beneficial to experience strong feelings of attraction at the beginning of a relationship, to help an individual focus on only one person, and in effect preserve energy spent on courting and mating. Biologists have observed this in both animals and humans, along with other similar behaviours, indicating that extrapolating evidence from animal research to humans, may be a valid approach. Research into attachment, for example, commonly uses prairie vowels as subjects, and these studies have noticed oxytocin and vasopressin levels change, during bonding behaviours. In humans, such bonding behaviours would be equivalent to sex, breastfeeding and childbirth. Nevertheless, even within the prairie vowels species alone, individual differences in hormone secretion can be seen, due to genetic repression. Therefore, it may not be valid to extend these results to humans, whose genetic code differs even more.

Chemistry
Chemistry as a discipline has also made its attempts at explaining “love”. Through the use of MRI’s and PET scans of human brains, studies have found that dopamine levels increase, during sex and when an indivdual spends time with their loved ones. There appears to be a correlation between dopamine levels and the sense of euphoria felt by those in love, yet the relevance of this evidence is questionable. Dopamine is also released during drug consumption, and as drug sensitivity varies, sensitivity to love may vary too. Potentially, the results from measuring dopamine levels are therefore completely relative and not sufficient evidence to prove a common trend. Further, research suggests that that only the optimum dose of dopamine will lead to the positive emotions connotated to love, while excessive amounts can cause irrationality and feelings of jealousy Therefore, without an absolute scale, this medium becomes very difficult to calculate, and generalisation beyond a study group, would be unrepresentative.

Mathematics
Another scientific discipline that has attempted to obtain quantitative evidence regarding romantic love is mathematics. While in a more abstract way and less empirically-based, some mathematicians have tried to unscramble the components that take part in making a relationship enduring. One of the most accepted is the Gottman equation: Gottman equation: The Gottman equation described by John Gottman is a nonlinear difference equation that intends to model the optimum amount of Marital Interaction. This equation was also later used by the mathematician Hannah Fry, from the Centre for Advanced Spatial Analysis at University College London. The equation has this form: W*t* + 1 = W + r*WWt* + I*HW(Ht*) for the wife's reaction and H*t* + 1 = H + r*HHt* + I*WH(Wt*) for the husband's reaction (they later clarified that despite of the names of these equations they apply to any couple independently of their gender). These equations are based on three factors, the partner's mood when alone + partner's mood when with partner + partner's influence on the partner's mood. This equation describes that the most successful relationships are those with a low negativity threshold, where couples allow each other to complain in order to discuss and work on their differences.

Conclusion
While hormones and neurotransmitters can be tracked, plotted in graphs and systematically analysed, it is difficult to make effective use of the numerical results obtained, as they are not fully representative of all humans. They exclude social and cognitive factors, making them reductionistic, and overall a purely quantitative approach may feel inappropriate, as it undermines the uniqueness associated with experiencing love.

Introduction
The application of science-based evidence in the analysis of archaeological remains helps us maximize the potential of the pieces. The interaction between these two disciplines has increased in the last decades, and through the combination of scientific experiments, and techniques with the knowledge and qualitative study performed by archaeologists, the informative potential of the remains has grown exponentially. Some examples are the analysis of ceramics, pigments, textiles, construction materials, and residues in archaeological environments, contributing to the historical reconstruction of the archaeological site.

Phosphorus and human activity (Chemistry)
In the past, human activity broke and disrupt the phosphorus cycle, which provoked an increase in the level of organic phosphorus in the soil. Phosphates accumulate very quickly in the soil, and they are able to remain for millennia in archaeological sites. Phosphates derived from human activity have mainly three origins: excrements, remains, and corpses (bones, meat, fish, plants...) and fertilizer. The degree of concentration and extension of the phosphates in the soil can indicate the extent and intensity of the human occupation that took place in that location.

A factor that affects the natural phosphorus cycle is the exploitation of the fields around these settlements. The form of exploitation can increase or decrease the amount of phosphorus in the subsoil, allowing us to recognize the agricultural methods of the time. .Livestock on the contrary decreases the amount of phosphorus accumulated in the natural soil, due to the continuous growth of vegetation.

Study of osseous tissue (Biology)
Bones are dynamic tissues, and their growth varies in response to internal and external factors during the life of the organism. The particular growth of a bone and its mineralization gets captured in the microstructure of the bone, making the osseous system the main source of knowledge in paleobiology. With the study of the reserves of proteins and nucleic acids in them and their morphology, hard tissues provide abundant information about the development, physiology, and lifestyle of the organisms.

One of the key ways of studying bone tissue is by the analysis of osseous microstructure in transversal sections of the bone. The microstructural organization of bone tissue reflects the influence of several factors like the organism's development, movement, interaction with the environment, and phylogeny. The microscopical analysis of cross-sections of bone allows us to identify characteristics related to the morphology of the organism such as vascularization patterns or the tissue organization degree, which helps us decipher some elements of the individual’s life, such as their state of development. Skeletochronology also provides information about the person’s age of death, the age they reach sexual maturity, and whether they went through periods of food shortage.

Data processing and mathematics (Computer science)
Since the birth of computer science as a discipline, every area of study has been granted the opportunity to expand their work through its methods and tools. When it comes to archaeology, this encounter began in 1955 with the launch of the first application of data retrieval systems in archaeology, by Jean-Claude Gardin. Later in 1957, he founded the Center for Documentary Analysis in Archeology (CADA).

Since then, digital data analysis has become crucial in the field of archaeology. Some of the techniques used in computational archaeology nowadays are Statistical tests, Bayesian statistics, Graph theory, Mathematical modeling, etc. An example of this is the use of the [https://en.wikipedia.org/wiki/Coefficient_of_relationship#:~:text=The%20kinship%20coefficient%20is%20a,alleles%20are%20identical%20by%20descent. kinship coefficient] (fθ = 1 – e^(‐t/2N)), which helps measure the relatedness between populations, helping the archaeologists deduct when two populations broke away. With that equation, you can obtain an estimated time of separation (t = –2N log (1– fθ) ).

In conclusion, with the combination of sample data, for example of the phosphorous in the soil (which involves a laboratory), site data, which involves the knowledge and fieldwork of an archaeologist, and computer data, which involves an engineer capable of operating with computer software; you can achieve as much data and information as possible from archeological remains. This is a perfect example of how humanistic disciplines can benefit from the advances of science and technology, while still remaining completely essential to the obtainment of knowledge in that field.

Introduction: Measurements of Wellbeing
Well-being usually refers to healthy, happy, satisfied life.

Since WWII the main measurement has been GNP and GDP, which is very much quantitative and based of financial wealth. For those reasons it has been criticized a lot due to its focus on economics rather than development and results in policies which increase economic wealth being seen solely positive and does not allow to be looked at more critically i.e. it does not take into account environmental costs generated by increased production, which might negatively contribute to public health which is included in the definition of well-being. Though economic situation is an important factor, once a country reaches a minimal economic wealth it becomes less and less significant. Therefore, there must be more social measures taken into account.


 * Education - it plays a pivotal role in well-being. It is not only a factor that increases job prospects, community involvement, but also it is a factor for increased health. It increases a likelihood of mothers vaccinating their children, better nutrition and decreases mortality rates.


 * Health - as component of well-being health is highly impacted by environmental factors. Air and water quality, proper housing and sanitation are health as well as not as straightforward factors as food and urban environment that might push towards less healthy lifestyle.

Though income, education and health are usually seen as the main drivers of well-being there is little evidence that in most developed countries these factors increase overall contentment. This conclusion suggests that it might be worth looking at more subjective measures.


 * Employment - there are numerous factors besides financial stability influencing the quality of job. Working environment, career prospects, relationship with colleagues, etc. These factors though could be quantified it may cause a loss in representation.


 * Gender - it is widely known that situation with gender equality is getting better; however, women are still under-represented and it tends to be unlikely for them to reach top positions in their careers. On the other hand, men are also affected by the gender gap. With changing expectations, they face a lot of uncertainty and instability.

Overall, there are potentially countless aspects of well-being that could be considered and a huge problem arises because some are primarily quantitative but others though could be quantified are very subjective. It might cause misrepresentation of well-being.

Gender and Wellbeing
As well as the dealing with the burden of the glass ceiling preventing women from reaching top positions in their careers, other factors such as education and health are affected by gender, consequently affecting wellbeing.

Education
The gender education gap is a major factor in producing gender inequality in ability to pursue higher education, income and career position. Starting from school years, sociologists have found that girls outscored boys on maths tests which were graded anonymously, however, when the teachers knew their names, the boys outscored the girls. Another sociological study found that science faculties hire twice as many men compared women with identical resumes and qualifications, men were also offered a higher salary and more mentoring opportunities.

Health
Gender has a large impact on health, through the negligence of the difference in physiology between men and women and the discrimination of women in diagnosis and treatment. On average, women wait longer for diagnoses and treatment, are half as likely to be treated during a heart attack, and are up to 3x more likely to die following treatment. Medicine has constantly had an androcentric viewpoint when approaching health problems, with 80% of pain studies being conducted on male mice when 70% of chronic pain patients are women, 5x as many studies published on male sexual pleasure than female sexual pain and 80% of drugs being withdrawn from the market due to negative side effects in women from testing only on male subjects.

Issues in evidence
Studying gender and wellbeing poses various difficulties in obtaining and interpreting evidence; for example, gender inequality in health through quantitative evidence may suggest that women are simply more susceptible to heart attacks, therefore they are more likely to die, rather than looking into the lives of women in similar positions who have had their symptoms dismissed as hysteria or anxiety and are not treated. This is also the case for gender data gaps in different health conditions, where certain conditions seem to affect men more, simply because they get diagnosed more. Furthermore, quantitative evidence in education may suggest that women are just not interested in achieving high-earning positions or pursuing higher education, due to a lack of insight into personal accounts of women's ambition and experience of discrimination. Quantitative evidence such as statistics are most often used to study these topics, however, there is a clear lack of insight into women's experiences behind the numbers and the root causes of gender gaps and inequality, influencing wellbeing.

Eye-witness Testimony as Evidence in Court
===Case of Jennifer Thompson === An important case study that helps invalidate observation as a reliable argument in court, as well as brings together the disciplines of law and psychology, is the case of Jennifer Thompson. In 1984, at the age of 22, Thompson was raped in her home by an unknown man who broke in. Thompson vividly described the experience to some psychologists years later, claiming she tried to be as alert as she could and memorise defining characteristics of the rapists appearance, so that she could later identify the assailant and he could be convicted. Following police investigation, Thompson immediately identified the rapist in a line up-a man named Ronald Cotton. However, 13 years later, through DNA testing, it was found that the real culprit was Bobby Poole, a man Thompson did not recognise. This shows how eye-witness testimony is in fact not as reliable as it is believed to be, as it may be affected by biases or preconceived notions that interfere with the accurate storage of information in the brain.

The Schema Theory
A psychological explanation for the error Jennifer Thompson made could be the Schema Theory.Schemas are mental representations that organise knowledge, beliefs and expectations stored in our memory. The theory states that schemas help simplify the complexity of the information we receive by adjusting or generalising it to our preconceived understandings. According to the theorists, humans assimilate and accommodate new information to existing schema. This results in stereotypes and a wide array of biases causing misinterpretation of information. In the case of Thompson, it is possible that her preconceived notion or schema of what a criminal or rapist should look like, interfered with her registration of the exact appearance of the man she saw. Even though observation is one of the most common means of obtaining evidence in not only law, but natural and human sciences as well, psychological schemas and biases argue that true evidence may be unintentionally but heavily influenced by the researcher.

The conflict between qualitative and quantitative evidence in court
The qualitative evidence provided by eye-witness testimonies, is evidently flawed, and when DNA testing, particularly post conviction DNA testing, became more frequently used in the judiciary system, it was found that this inaccuracy had led to multiple innocent people being wrongly sentenced .Such mistakes can have detrimental impacts on individuals' lives, but also lead to a lack of trust and overall negative perception of the justice system. This realisation left the justice system faced by a new conflict, regarding whether qualitative evidence should be prioritised as highly as quantitative data, which is considered more subjective, or whether it should be excluded completely.

Observation
The principle method behind eye-witness testimonies, has been an intrinsic part in scientific research all throughout history. Theories that are nowadays considered as proven, were often founded purely on observation. With other testing methods not yet available, humans had to rely on their senses and the inclination to trust and believe in the reliability of brain systems was required. The suggestion that visual perception may not be as reliable as thought, has thus been difficult to accept, particularly because it also raises uncertainty as to whether other senses can clearly mirror reality. What differentiates observation within a scientific environment, from eye-witness testimonies, is however the criteria of unexpectedness. Arguably, this is why eye-witness testimonies are rather subjective. Witnesses' accounts are often impacted by emotions and biases, which can distort memory, but it is difficult to examine when this has happened. This makes it tempting to completely disregard eye-witness testimonies, and so exclude any false information they may provide. Yet, this also explains exactly why this would be inappropriate.

Bias of witnesses
Witnesses feel a personal connection to their memories, enhanced by strong emotions of anger, fear, or shock and specifically if they are the victim of a crime, they want to ensure the suffering they experienced is reflected in their statement. Completely disregarding eye-witness testimonies, would undermine this emotional factor and could lead to victims feeling not fully represented in the courtroom. In search of finding a balance, modern science has thus tried to model systems that can quantify this uncertainty, and calculate the probability of an account being correct. To reduce human error, they have tried to take a computational approach, one such method being SEM (the semantic evaluation method). This method tries to quantize the originally quantitative evidence, in an attempt to make it as objective as possible and still valuable in court.

Conclusion
While conflicts regarding which should be prioritised, remain, both qualitative and quantitative methods have found their role in the processing of a trial. There still is discord as to whether probabilities should be used to define how true someone's statement is, and whether this in itself is an accurate representation. However, it appears that this is a disagreement that can only be solved in the future, if the disciplines of science, psychology and law cooperate to figure out how to make eye-witness testimonies objectively valuable.

Manipulation of Statistics
Statistics is often viewed as an ultimate mean to present evidence. When evidence is quantitative and maths-based rather than qualitative, it is easier to believe in. Techniques of data representation in statistical research can often be flawed. Consequently, there is a huge amount of statistics that is unjustified but still presented to the general public, creating the spread of fake news and unreasonable opinions. Unfortunately, not many people are willing to fact-check and analyse the information that they read, particularly, on internet. And not only an ordinary reader can fall victim to misuse of statistics, but even professional scientists can sometimes be decieved.

It was already proven that manipulation of statistics is very easy and common, particularly by Darrell Huff, the author of the book How to lie with statistics . In this book, he described the ways that are used to make information more appealing, to take the necessary parts of the research, leaving the unnecessary befind, and to misuse statistics in order to deceive the audience and manipulate their opinion. Misuse of statistics can be best described as "using numbers in such a manner that – either by intent or through ignorance or carelessness – the conclusions are unjustified or incorrect." The implementation of false evidence via misuse of statistics is common in media. Darrell Huff described many methods that can be used to manipulate the numbers, from non-representative sampling and manipulation of processing to overgeneralization.

Covid-19 Statistics in Media
In order to track how statistics have been manipulated for self-serving purposes, we can look at the example of the coronavirus and trace how the russian governmental media have described the situation. The Russian authorities claimed that the reason of low numbers of deaths during the first wave in spring was the high quality of healthcare in the country. However, the pathologists who perform autopsies state that they have been concealing the cause of death because of the instructions from the Ministry of Health. For example, if the cause of death is pneumonia that was caused by coronavirus, the documents will state 'pneumonia', rather than 'covid'. Demographers who study Russian health statistics believe that this is deliberate manipulation of data caused by the federal government that distorts the picture of the pandemic. These kinds of distortions are not uncommon in the Russian media. They became especially widespred after Vladimir Putin's "May 2012 Decrees", that obliged the regions of the country to reduce mortality from certain diseases.

Moreover, during the second wave of coronavirus in autumn, in St. Petersburg, for several weeks, the daily number of people recovering from Covid-19 have been half of the daily number of cases. This suspicious pattern has been noticed by local media, but even after their publications, the strange ratio in the statistics of the coronavirus remained the same. The local authorities did not explain this strange pattern, only noted that daily statistics may not be completely accurate, due to the heavy load in hospitals and the delay in documenation.

Consequences
As a result, it is not only impossible to state with complete certainty what is the number of cases, but also to make sure that the health care system is able to manage with the large flow of patients. Using this statistics, the government officials can easily say that the country is able to provide everyone with sufficient health care, when it is clearly not so.

Biology of Happiness
Happiness can be defined as pleasant bodily sensations in response to external stimuli. These bodily sensations are a result of the action of several neurochemicals, mainly dopamine, serotonin, norepinephrine, melatonin, endorphin, and oxytocin (hormone). Studies also suggest that genetic factors could be responsible for as much as 50% of happiness: the “5-HTTLPR and MAO-A genes”.

In this sense, happiness is a universal human experience, as we are predisposed (genetics, biochemical factors) to experience happiness, even if some of us are genetically favoured. Happiness can be measured using quantitative evidence, as Mark Holder has done using biological indicators of the aforementioned neurotransmitters/hormone.

Cultural Construct of Happiness
Qualitative evidence for happiness suggests subjectivity: what defines happiness varies across cultures. Happiness, rather than what the previous paragraph would suggest is “situated and embedded in cultural context”, and therefore one's happiness is contingent on certain expectations set in a cultural frame. The same experience will be perceived, processed and reflected upon in different ways by people of different cultural backgrounds.

Variations in experiences of happiness across cultures, are not just geographical, but also generational. Cultures, their morals and customs are everchanging. With a progressive society, comes new emerging notions of happiness. The idea of happiness itself is closely related to what the ideological superstructure dictates. In a capitalist society increase in income is perceived as a constant goal, and praised culturally (increase in status). But this constructed idea of happiness can only be temporary, as it comes with “hedonic adaptation and social comparison”. The idea that consumption can buy happiness is deeply rooted in culture and capitalistic values of status enhancement through symbols.

Interdisciplinary approach
While happiness is measured through neurotransmitters and hormones in Biology, producing quantitative evidence, social constructivist disciplines such as Anthropology and Sociology view happiness as having a more social and environmental underpinning and see it as more subjective and individual, therefore they would likely use qualitative research methods such as unstructured interviews with open-ended questions. An interdisciplinary approach is required as it is necessary to understand how happiness is related to physiological and biochemical events, and also to understand how this is subjectively felt by the individual. However, there may be several problems encountered when conducting interdisciplinary research in this context, in relating the quantitative evidence from Biology to the more qualitative evidence in social constructivist disciplines. It is difficult to deduce a correlation, for example, concerning the production of a given neurotransmitter with the level of happiness the individual felt. It is uncertain as to how each individual will define and interpret the word "happiness", and how each individual subjectively feels happiness. This would require further qualitative evidence to allow the individual to elaborate on their personal experience and interpretation of happiness, however this would result in the data being harder to correlate with the quantitative evidence from Biology. Furthermore, simplifying each individual's explanation to make it easier to analyse against quantitative evidence risks the loss of the purpose of qualitative evidence in understanding, as accurately as possible, an individual's internal state.

Male superiority
Charles Darwin and his cousin, Francis Galton, both used their science to support the theory that women are innately inferior to men. In Darwin’s “The Descent of Man” he wrote that men are "more courageous, pugnacious and energetic than woman [with] a more inventive genius. His brain is absolutely larger" and "...man attaining to a higher eminence, in whatever he takes up, than woman can attain-whether requiring deep thought, reason or imagination, or merely the use of the senses and hands...Thus man has ultimately become superior to woman.”. Galton studied differences between the sexes . Angela Saini wrote about Galton and men like him: “By gauging and standardising they coated what might otherwise have been seen as ridiculous enterprises with the appearance of scientific respectability.". This describes how evidence can be created by quantification, and how quantified evidence lends credence to theories. Darwin believed that, as he and later Angus J. Bateman and Robert Trivers, had observed in animals that males had to compete for females’ attention. Darwin bolstered this by his observations that men in Victorian England were more competitive than women. They believed this put a greater evolutionary pressure on them, and therefore men are more evolved than women and males who have multiple mates have an evolutionary advantage. This is combined with theories that the relative abundance of sperm compared to ova, men are meant to have more sexual partners than women as women invest more in each child.

The difference in size and upper body strength between men and women has also been used in many instances as quantitative evidence that men are naturally stronger and more dominant while women, needing male protection, are more submissive.

However, if the role of society in the use and interpretation of evidence is considered, a different weighting is given to such conclusions. Darwin and Galton were influenced by the society they lived in in which women were viewed as inferior to men. Their theories were constructionist; justifying the inequalities of Victorian society. In today's society papers claiming to have proven differences between men and women still get a lot of media coverage, despite the statistical manipulation, small sample sizes and conflicting evidence often used.

Evidence conflicting with male superiority
Evidence is also affected by how it is collected and who by. As the proportion of women in scientific and social-science disciplines increases, there in an increasing canon of work which refutes the preconceptions about the roles of men and women.

There is strong qualitative evidence that patriarchal societies are not the natural norm. Anthropological studies of other societies such as the Himba of Namibia and the Mosuo of China and the Bari of Venezuela have partible paternity. All of which show that patriarchal societies and nuclear families are not the default. Although the qualitative evidence of anthropology is generally viewed as inferior to quantitative evidence, it measures factors and promotes an understanding of interactions that is lost in quantitative evidence. Moreover, consistency with which exceptions in humans and other animals are found makes the findings credible.

There is also quantitative evidence that, although most men may be physically stronger, women are not the weaker sex. Women live longer than men. Boys are 14% more likely to be born prematurely than girls, probably because hypertension and placental problems are more common if pregnant with a boy. Premature boys are more likely to be disabled than premature girls. They are also less likely to survive at every age group

Excluding parasitic mating, no species is completely monogamous. Both male and female bonobos and chimpanzees, humans’ closest relatives, have multiple sexual partners. Anthropological studies have found that there are several anatomical, physiological and behavioural adaptations which humans share with those primates, which indicates that humans evolved to be polygamous too. This supported by quantitative evidence which found that primates with female copulatory vocalisation and similar size differences between the sexes also have sperm competition and hence both sexes multi-partner. Polygamy is advantageous for both sexes from an evolutionary perspective because it ensures genetic diversity in offspring, hence an increased likelihood of survival.

Continued impact of inequality in health
The legacy of biased scientific evidence continues to have an impact on other disciplines, such as medicine. There is strong qualitative evidence from patient and doctor accounts, as well as quantitative analysis of disease in populations, that shows that diseases present differently in men and women, Throughout history the health issues of women have been dismissed as hysteria. Women are more likely to have adverse effects from prescribed drugs than men this is because the evidence collected to determine safety and efficacy is mostly based on men. In the U.S.A. in 1977 the FDA prohibited the inclusion of fertile women in clinical trials, except in life-threatening scenarios. This was not overturned until 1993. And even today clinical trials are skewed towards white men.

Neuroscience and gender differences
In neuroscience there is continued debate over brain differences between men and women. Although men tend to have larger brains, this is in line with their larger body size. It has not been shown that differences in brain size between humans makes any functional difference. Other variances have been found. Women have a greater proportion of grey matter and men, white. Women have greater 15-20% greater blood flow Inferences have been made that this means that men are better at spatial reasoning, for example, and that women have better verbal memories. However, this does not represent the majority of neuroscience research, and there are flaws in the evidence gathering, fMRIS, used to detect blood flow in the brain can easily be influenced by noises and are vulnerable to false positives and their resolution is very poor - the maximum resolution would include 630,000 neurons. The flaws of fMRIs are demonstrated by ‘the dead fish experiment' which showed areas of activity in a dead salmon’s brain. Brain differences between men and women are not particularly obvious, or able to be interpreted simply. The involvement of forward and reverse inference, in which conclusions about what brain activity seen on an fMRI scan means, are vulnerable to the biases of their interpreters. Therefore it can be concluded that most differences between men and a women are caused by society, not brain differences or evolution. Additionally lots of evidence that seems to support the theory that women are inferior to men has not been able to be replicated, and is done on very small samples, which impedes its reliability as empirical evidence. Moreover the plasticity of the brain has been proved by people maintaining full mental function after having semi-lobotomies as young children and MRIs of London taxi drivers show they have a larger hippocampus, showing that environment changes the structure of the brain and hence any differences found between the sexes could be caused by society.