For better or worse; changes in Employment & Support Allowance prognosis

I've had far too many Work Capability Assessments. I think I've had something like 8 since 2010, mostly done on paper. My condition has either not changed substantially, or gotten worse. It struck me that this has never been reflected in the results of my WCA.

Take my latest one. My original prognosis was 2 months, then went up to 2 years and finally "indefinite". My health got worse, and on the urging of Relevant People, I tried to get into the Support Group. I failed, and my prognosis was reduced to 18 months. The council's advisor said this was likely a punishment for daring to question them (no, really.)

I did what I always do when I'm annoyed - moan on Twitter. After that, I had a look for data on changes in ESA prognosis. There wasn't any, so I began an annoyingly drawn out Freedom of Information case against the DWP. It ended up with the Commissioner having to intervene to get them to give me the data after ignoring me for months on end.

Raw	WRAG	SG	FFW	Percentages		WRAG		SG		FFW
No change	56,500	12,100	91,700			17.91		3.84		29.07
Increase	78,200	37,300				24.79		11.83
Decrease	24,400	6100				7.74		1.93
Terminal		600						0.19
Unknown	6,200	2,300				1.97		0.73

Table 1. Prognosis and WCA outcomes for people originally assigned to the Work-Related Activity Group.

Raw	SG	WRAG	FFW	Percentages	SG	WRAG	FFW
No change	47,700	6,400	23,400		23.18	3.11	11.37
Increase	90,400	8,600			43.93	4.18
Decrease	13,900	4,800			6.75	2.33
Terminal	2,600				1.26
Remain	1,100				0.53
Unknown	5,900	1,000			2.87	0.49

Table 2. Prognosis and WCA outcome for people originally placed in the Support Group.

Prognosis Change	Total	Percentage
Fit for Work	115,100	22.49
No change	122,700	23.98
Increase	214,500	41.92
Decrease	49,200	9.62
Became terminal	3,200	0.63
Remain terminal	1,100	0.21
Unknown	5,900	1.15
Total	511,700	100.00

Table 3. Changes in prognosis across all groups.

You'll notice a few things that seem a little bit off. For example, 4.2% of people in the Support Group are reassessed and placed in the WRAG, but with an increased prognosis? 2% of people being placed in the Support Group after being in the WRAG have a decreased prognosis - their condition is worse, but more likely to improve?

20% of WRAG claimants and 25% of Support Group claimants are given the same prognosis in later assessments, despite the fact that the prognosis was evidently wrong the first time. 50,000 people (~10%) had their prognosis reduced - the HCP decided they were likely to improve in a shorter length of time, despite being unwell longer than the previous HCP had estimated.

The DWP says that the prognosis given is just how the schedule assessments, but if you've seen a WCA report, you will know that the prognosis is the the time at which the assessor thinks the claimant will be able to get a job.

The prognosis system is important for claimants. It determines the frequency of assessments (a massive strain in itself), but also the claimants' conditionality. Lower prognoses trigger the claimants' "eligibility" for the Work Programme. This data shows that there is little consistency or logic in how prognoses are determined. In 10% of cases, the HCP is predicting a faster return to work than previously, despite no improvement in health or, sometimes, even a significant worsening.

Non-24-Hour Sleep-Wake Disorder Awareness Day - The World Spins Madly On

"I just got lost and slept right through the dawn, and the world spins madly on"

The World Spins Madly On, The Weepies

Today is November 24^th. It is also the ‘Awareness Day’ for Non-24-Hour Sleep-Wake Disorder, a rare and "extremely debilitating" circadian rhythm disorder. We have no idea how many (or how few?) people are affected by it, or how to even treat it.

There has been a fair bit written on why 'Awareness Days' are, in general, a bit rubbish, self-indulgent and excessively corporate and fundraising-y. I generally agree, but I'm going to defend this one (and a few others) - N24, like many things, is rare enough that not even doctors have heard of it if they don't specialise in the area and our suffering could be so significantly alleviated by understanding and accommodations - and this can only happen once people are 'aware'.

I'm also not raising money and, unlike a lot of 'Awareness Day' stuff, I'm someone with the condition under discussion. This is us trying to make our (and other people's) lives better, and not get Good Samaritan Browniepoints while ignoring the issue for the rest of the year. This is a daily struggle, and one without end.

I'm also only really dealing with N24 as it affects sighted people, because Sighted N24 and No-Light-Perception N24 should be considered different conditions. 

N24 Awareness Day feels particularly important to me this year, due to a (hopefully innocent) campaign of misinformation which is also why I'm focussing only on sighted people. When I published a photo of my latest research submission, I got a comment of surprise that N24 could affect us. This is because of a pharmaceutical company which has a license for a drug to treat N24 in NLP people only. Their adverts describe N24 as something that only happens to blind people, and it went so far as getting regulatory agencies (eg FDA, EMA) to define N24 as "occurring in blind people". This is patently not the case (the first reported case of sighted N24 was in 1971) but this myth is getting traction.

This culminated in that drug company donating money to America's National Sleep Foundation which then produced an absolutely atrocious website  with the gem "N24HSWS is transient, reversible, and may be associated with a psychiatric disorder in sighted subjects".

Awareness is the opposite of ignorance. Hopefully some awareness will fight against that ignorance.

1: What is N24?

N24 is a chronic disorder characterised by a circadian rhythm that differs from 24 hours - the vast majority are over 24 hours but cases of less than 24 hours exist. Mine, for example, is 26 hours.

2: but what does that mean?

The circadian rhythm is your 'body clock'. It controls every time-related function of your body - it controls your blood pressure, appetite, and more subtle things like cortisol secretion. Most obviously, it affects sleep. Your circadian rhythm is the mechanism by which you fall asleep every night and wake up every morning, and it reacts to light and darkness to make sure this happens.

For whatever reason the circadian rhythm isn't 24 hours, that causes the time-linked biological functions to vary by how far off 24 hours it is. My circadian rhythm is 26 hours so, relative to the 24 hour clock, my biological functions get two hours later each day. I fall asleep at midnight one day, then 2am the next. Then 4am, 6am, 8am.. ad infinitum. Below is a copy of my 'actigraphy' (the standard diagnostic test for N24, a wrist-worn accelerometer that measures movements. Fewer movements = sleep) showing this pattern.

3: Okay, so why is this bad?

Being forced into functioning in the typical 24 hour pattern causes us a great deal of (physical and psychological) distress. Following our own pattern causes us a great deal of psychological distress, and severe difficulties with employment, interactions with society, education, relationships.

There is a harrowing case study (n24 is so rare that case studies are often all that is possible) of someone who developed N24 symptoms as a child - he had been misdiagnosed with multiple conditions, including "depression, schizotypal personality disorder, and learning disabilities". He was described by a psychologist as:

"being extremely introverted with severe narcissistic traits, poverty of thought, and disturbed thinking, including thoughts with persecutory content and self-destruction that led to a paralyzing anxiety, anhedonia, social isolation, and withdrawal"

When he had been successfully treated (a rarity in itself, unfortunately), there was no evidence of psychopathology. Hopefully this gets across the horrific effects of the long-term sleep deprivation we are often forced to endure, but there are physical effects too. Shift workers are very useful for studying the health effects of inflicting circadian disruptions on people - and shift work has been linked to various cancers, endocrine disorders and cardiovascular disease.

I've got my own research, currently under peer review at the journal Qualitative Health Research, which shows the harmful psychological and 'quality of life' effects the nocturnal phases of N24 have, but others have noted that, despite almost universal and severe difficulties with education and employment, depression symptoms alleviate when the person is in their 'dirunal' (ie awake during the day) phase.

4: How is n24 treated?

Treatment is more frequently successful in N24s without light perception, because their condition is due to a disruption in the light-suprachiasmatic nucleus-pineal gland system and this can often be helped with melatonin or other similar drugs (eg the recently licensed tasimelteon - it hasn't been tested, but I'm willing to go on record as predicting it to not be significantly different from melatonin. It only entrained ~30% of blind N24s, if memory serves. I can't find the FDA documents again).

Few treatments are studied in sighted N24s and those that are have very weak, if any, evidence for their usefulness. The standard approach is melatonin and bright (10k) lux, but the evidence for their effectiveness is case studies, and for every supportive case study there is a negative one. Basically, 'it'll work sometimes' but as my own neurologist said, "[n24] is very difficult to treat and keep under control, with short-term relief usually only possible with short courses of strong hypnotics and stimulants" [his full letter is at the bottom, it's a good brief description of n24].

How is N24 treated? It's a crap-shoot, and it usually doesn't work anyway.

5: What would make your life better?

Precluding a wonder-drug that allows entrainment in the absence of debilitating symptoms that sometimes accompany it (eg extreme tiredness), there are two things that would be most helpful, and these stem from awareness.

The first is compassion. Our lives are a struggle and more often than not we are blamed for it, by everyone. We are blamed by our parents and teachers, our doctors and employers. We're "lazy", "inconsiderate" "scroungers" who "just don't try hard enough".

This is partly based on the way society misunderstands sleep - people believe they are in control of their sleep. They think they can chose when stay awake and when to sleep, but they can't. They don't see that because, as a general rule, their sleep falls within the boundaries society is built to accept. They'll usually complain about "waking up too early on their day off" or "not being able to get to sleep" but never seem to put two and two together. You can put yourself in a situation where you are more likely to sleep, but you can't make yourself fall asleep.

But because people think they are in control of their sleep, they think we are too and thus we are to blame for missing work, or sleeping through an appointment, or spending the day in bed instead of going clubbing with you. We internalise this blame, and we hate ourselves.

The second is societal change and accommodations. In a lot of areas, this seems to be going in he right direction, albeit to a small degree. 

Work hours are becoming more flexible, but it's not enough. Employers still demand work be done "during the 9 to 5 (or 7 to 3)" when it could be done just as easily and well at any time, even if the person is allowed flexible working hours or to work from home.

We're allowed to book doctor appointments on-line during the night, but we need to do it days and weeks in advance when we won't have a clue what state we'll be in (and this consequently affects the appointment and our test results, eg blood pressure, hormones, etc).

24 hour shopping is becoming more commonplace, but is meaningless when public transport stops for 10 hours at 9pm, as many N24s cannot drive due to safety risks.

Life is much less lonely now we're able to socialise on the Internet at any hour of the day but this is no substitute for face-to-face interaction for those that need it.

There are so many little difficulties and they all add up. We'll often ask you if you can make a change to your procedures at work and so on, and they'll usually be little things like "don't discharge me from my sleep disorders hospital clinic for sleeping through an appointment".

In general though, ask yourself this: could someone nocturnal and with little ability to plan in advance use my shop/work for me/access, as easily as others, the service I provide? If the answer is no, you'll spot ways you can make the life of sighted N24s* a little easier.

*and people with Delayed and Irregular CRDs, and NLP N24s, and countless other sleep disorders and things that cause severe tiredness and fatigue.

Edit: Doctor's letter!

Bias in the Work Capability Assessment: Analysis of Results of 1,000,000 WCAs

Update 14/09/2015: I've added a bit at the bottom.

Abstract

The Work Capability Assessment (WCA) of Employment and Support Allowance (ESA) is the legal test by which eligibility for ESA, the UK’s social security benefit for those unable to work due to illness or disability, is determined. This is an update of my previous analysis, including an extra 200,000 results, of Incapacity Benefit claimants being migrated over to ESA. All the data is from freely-available government datasets. I show that there is significant bias towards the poorest and most disabled in the WCA and this must be urgently addressed.

Introduction

In 2013 and 2014, I conducted a statistical analysis of the outcomes of the Work Capability Assessment for Incapacity Benefit Claimants being migrated to Employment and Support Allowance on my old blog. I showed significant relationships between WCA judgements and variables like life expectancy and local rates of poverty, and interpreted this to mean that the WCA is biased against people in poorer or less healthy areas.

Since that analysis, I’ve learned that the United Nations are investigating the UK for “grave and systematic” abuses of the human rights of disabled people; a group in which I am included. What better time to update that analysis?

There are numerous variables which ESA should logically be related to.  The most immediately obvious is local rates of disability and health. There should be a higher proportion of people being found fit for work in healthier areas, with lower disability. Conversely, there should be a higher proportion of people going into the Support Group in areas with lower life expectancy and higher rates of disability.

There have been accusations that the WCA is not a valid assessment of disability. If this is the case, there will be relationships with variables other than disability. In the UKs current political climate, cutting government expenditure has been touted as one of the key goals of both governments since 2010, when ESA began being rolled out on a wide scale. As the majority of people getting ESA are poor (and get income-based ESA), I have chosen to test relationships with financial deprivation and, at the suggestion of an ESA whistleblower, I have chosen to test the relationship between WCA outcome with educational attainment; their suggestion was that people with better educations are more capable of getting into the WRAG and Support Groups.

Method

I collated data from various government sources (full details are in the data provided) including Public Health England and the Department for Work and Pensions. I designed the dataset to show relationships at the Local Authority level as this was the most consistent level of abstraction used amongst the various sources of information. I chose to combine the deprivation variables into a composite measure, averaging out the Local Authority residents in the 20% richest areas of England with the 20% poorest areas of England. In this composite measure, a lower score means lower rates of deprivation.

I then conducted statistical analysis using SPSS 20 and Microsoft Excel.

Descriptive Statistics

There is a great deal of variance between areas in the proportion of claimants that are put into each WCA category as shown in Table 1. In some Local Authorities, almost 50% of people are being judged fit for work compared to 25% in other areas.

	% Fit for Work	% WRAG	% Support Group
Mean	18.95	37.17	43.88
Standard Deviation	3.57	4.177	5.12
Minimum	10.87	24.72	33.24
Maximum	46.63	46.63	58.25

Table 1: Descriptive statistics for WCA Outcome rates

Correlations

I first chose to test whether there were relationships between WCA outcomes and the variables of interest to determine if it was worth conducting a deeper analysis, and this is shown in the correlation matrix (table 2) below. All results are statistically significant (p=<.05) and N=324. All tests are two-tailed.

	Life Expectancy	% with moderate or severe disability	Deprivation	% with 5 A*-C GCSEs
% Fit for Work	-.559	.315	.501	-.233
% WRAG	ns	.314	ns	-.239
%Support	.437	-.475	-.340	.358

Table 2. Pearson’s r correlation matrix of WCA outcomes with important variables. NS = not significant.

These correlations are illustrated below in Images 1, 2 and 3.

Image 1. WCA Outcome vs local life expectancy.

Image 2. WCA outcome vs local educational attainment

Image 3. WCA outcome vs local deprivation

Interim conclusion

It is clear that there is a complex relationship between the variables, given that the relationship between the test variables and WCA outcomes changes. However, it is also clear that the outcome of the WCA is not purely dictated by the levels of disability in an area; if this was the case, the proportion of claimants going into the WRAG and Support Groups would be positively correlated with the proportion of people with moderate to severe disabilities, and the proportion of people being found fit for work would show a negative correlation. This is not the case, and as the results show, the more disabled people there are, the fewer people are going into the Support Group and more are being found capable of work and having their benefit eligibility withdrawn.

Given the complex interrelationship between the variables, I have chosen to conduct three stepwise linear regressions, one for each WCA outcome. This will statistically control for the effect that, for example, poverty has on health, and will give us a clearer picture of what the true relationship between the variables is.

Regression Analysis

Fit For Work judgements

In this regression, both deprivation and the rates of severe disability contributed to a statistically significant model (R=.511, F(2,321)=56.595, p<.001). As deprivation increased, the rate of fit for work judgements also increased. As the rate of severe disabilities increased, the rate of fit for work judgements increased also.

Work-Related Activity Group judgements

In this regression, the proportion of people with moderate disabilities, the proportion of those with 5 A*-C GCSEs and local deprivation levels all contributed to a significant model (R=.408, F(3,320)=21.341, p <.001).

As deprivation and the rate of GCSEs decreased, the proportion going into the Work-Related Activity Group also decreased. However, as rates of moderate disability increased, so did the rate of people going into the WRAG.

Support Group

In this regression, both the proportion of people with severe disabilities and the proportion of those with 5 or more A*-C GCSEs were contributors to a significant model (R=.515, F(2,321)=57.911, p<.001).

As the rate of severe disabilities increased, the proportion of claimants in the Support Group decreased. However, as educational attainment increased, the proportion going into the Support Group also increased.

The regression analyses are summarised in Table 3, below.

WCA Outcome	Variable	B	Std. Error	beta	t	Sig.
Fit for Work	Constant	13.610	.754
	Deprivation	1.497	.226	.419	6.611	<.001
	Severe Disability %	.234	.117	.127	2.00	.046
WRAG	Constant	36.198	3.096
	Moderate Disability %	.981	1.63	.331	6.030	<.001
	GCSE %	-.114	.035	-.190	-3.238	.001
	Deprivation	-.704	.235	-.169	-2.996	.003
Support Group	Constant	44.411	2.960
	Severe Disability %	-1.077	.139	-.406	-7.735	<.001
	GCSE %	.140	.039	.190	3.615	<.001

Table 3. Final regression models and statistics for each WCA outcome

Discussion

It is clear that there is a complex and counterintuitive relationship between WCA outcomes and variables which should logically be related and others that should not be related. If the WCA were a fair and accurate assessment of disability, the proportion of people going into the WRAG and Support Groups would be positively correlated with the rates of moderate and severe disability in the local area. This is not the case as shown in Images 1, 2 and 3.

Image 4, below, further illustrates the relationship between economic deprivation and WCA outcomes. It is apparently that fit for work judgements occur more frequently in areas a higher proportion of their population living in the 20% poorest LSOAs of England, while the inverse is true of areas with fewer fit for work judgements than average.

Image 4. Proportion of people in poverty in areas with above or below average proportions of fit for work judgements.

Fit For Work Judgements

That fitness for work judgements decrease when the rate of severe disabilities in an area increases is a strong indictment of the WCA. If the test was valid, it would be expected that this relationship would be reversed. It is logical that, in areas with higher rates of disability, there would be fewer people found able to work. That this is not the case raises concerns about the validity of the WCA.

Furthermore, this decision is influenced by the affluence of the claimant’s area. It would be expected that ESA claimants are poorer than the general population because of the means-testing component but also because disabled people are generally poorer. However, this should have no effect on the outcome of the WCA; all these people are recognised as disabled and pass the financial or contributory criteria required to even undergo the WCA. It is a great concern that people in poorer areas – where social security benefits contribute more to the local economy – are facing more stringent or less fair WCAs than people in richer areas.

The ESA Groups

Once a claimant has had their WCA and hasn't been found fit for work, they are placed into either the WRAG or Support Group. What is most concerning here is the pattern of significant findings; it would be expected that the WRAG, for claimants “capable of work-related activity” but incapable of work, would be correlated with the proportion of moderate disabilities. However, the Support Group, for claimants “incapable of work-related activity” should be positively related to the proportion of severe disabilities, but is not. Instead, areas with higher rates of severe disability have fewer Support Group judgements.

Furthermore, educational attainment has a significant effect on both WRAG and Support Group judgements. Higher educational attainment in a local area correlates with more Support Group judgements, but the opposite is true of the WRAG. This suggests that the WCA outcome is somewhat influenced by the claimant’s experience or skill at navigating the bureaucratic structures of the Department for Work and Pensions, such as fully understanding all the questions of the ESA50 medical questionnaire. This is a variable that should have no effect on an objective and valid assessment of disability, and that it does is a concern, particularly considering how many disabilities start in childhood and the direct and indirect effects on education.

Limitations

As with all investigations, this one has limitations. Firstly, the data I have used is local averages, and this limits the conclusions that can be drawn. Were a similar investigation completed with access to full details of ESA claimants and WCA (points, claimants age and education, etc) it would be easier to see particular biases. Local Authority averages were all that were publicly available.

Secondly, this study has looked at some nebulous concepts (e.g. “health”). The use of surrogate variables is common, but is something to bear in mind when interpreting the data. For example, a drug to prevent heart attack might be tested on its ability to lower blood pressure, and from that it would be inferred it could prevent heart attacks. The rate of heart attacks is inferred from a third variable. This is what I have done with, for example, education. I am inferring the level of education in an area by the rate of high GCSE performances.

Conclusions

The Work Capability Assessment is simply not a valid assessment of disability and is unduly affected by variables which should, in theory, have no impact on the results. This is a source of great concern for disabled people. However, improvements to the method by which successful claimants are assigned to the WRAG or Support group has become more important since the Budget, when it was announced that new claimants placed in the WRAG would receive 30% less money, further impoverishing this already disadvantaged group.

As for the WCA itself; there are three key points raised in this analysis:

1.       The poorest are the least likely to get onto ESA at all, as areas with higher socio-economic deprivation have a higher rate of fit-for-work judgements.

2.       The assignment of claimants to the ESA groups has no relationship to the severity of the disability the claimants experience, as severe disabilities reduce the probably of a Support Group finding but also increase the probability of a fit-for-work judgement

3.       Educational attainment should play no role in the WCA, but higher educational attainment in a local area increases the number of Support Group judgements, which are preferred by Claimants for their lower conditionality and larger payments.

I believe I have shown that the Work Capability Assessment is biased, particularly against the poorest claimants who are more likely to ‘fall at the first hurdle’ and be found fit for work. However, the WCA also shows bias against the most severely disabled who it should be helping the most. That it can have such a relationship with educational attainment is alarming, and again this suggests a further bias towards those with better educations.

As others have said, the WCA needs an urgent overhaul or to be scrapped in its entirety. This analysis shows why: by favouring richer, healthier areas with better access to education, the WCA is reinforcing the systemic disadvantages faced by disabled people.

Extras

It's hard to get across how important this is using just numbers; a lot of people don't quite grasp that, behind each number, there's a person. That there's a correlation of r=.55 between two variables, with a p value of less than 0.000000000001 (literally!) means a lot to me, but not much to others, so here I'll be adding a few more graphs and such as I add new variables or come up with ideas that might help illustrate what's going on above.

My data is available here, and is colour-coded to show sources.

Here are two graphs; one shows the rate of early deaths in areas that most or least frequently give fit for work judgements.

The second shows the proportion of people living in either the 20% poorest or richest areas depending on whether that area gives amongst the least or most Fit for Work and Support Group judgements: In areas where there's the highest rate of fit-for-work judgements, over 35% of people are in the poorest areas, vs only 5% in areas with the lowest rate.

Deprivation

I've added a new variable to make the relationships with socioeconomic deprivation a bit easier to understand; in the future, I'll be talking about the proportion of local households with two or more indices of deprivation (such as low income, low access to good healthcare, and so on).

Targets

@BendyGirl, over on Twitter, raised the possibility that the relationships could be accounted for by targets used to control how many judgements WCA assessors can make. The short answer is: I'm not sure! It's not really possible to answer with the data available, but some of it is consistent with the idea of targets so they may well be a source of the bias I've found.

This graph, using the new definition of deprivation, is a good example.

What we see is WRAG judgements staying approximately the same, while Support Group judgements go down as poverty increases and fit for work judgements go up. This is consistent with the 'targets' hypothesis.

Assume an HCP is only allowed to make 1 Support Group judgement out of every 10 they make. Now imagine they're in an area where there are going to be a lot of claimants. They have no idea which conditions are going to come through the door next; they're pressured by the system to save that one Support Group allocation for someone who "really needs it".

They're therefore more inclined to place claimants into the WRAG regardless of how severe their disability is, in case someone worse comes next, but there's a target for the WRAG too! The WRAG fills up with people that should be in the Support Group, and there's nowhere for people who should be in the WRAG to go; they're found Fit for Work.

This scenario is consistent with the graph above, and the fact that the proportion of Support Group judgements decreases (and FFW increases) as the number of WCAs increases significantly, albeit weakly and with poor fit (Support Group r2=.032). If targets were having a strong role in the bias I've found, I would expect the r2 to be much higher. This is an example of a statistically significant result but one of dubious real-world relevance.

However, it's important to note that this data only includes the 'highest-level' decision. If the claimant went to appeal, then the tribunal's decision is the one recorded. Likewise, if the claimant hasn't had a formal decision by the DWP, then the HCPs decision is the one recorded. It's possible that targets are playing a minimal role, as tribunals are (to my knowledge) not subject to them; any bias introduced by targets at the HCP and DWP level would be would be undone by the tribunal decisions assuming the majority of people affected appeal the decision (as these were IB claimants being migrated to ESA, I assume most would appeal!)

It's also worth noting that the correlation between the proportion of Support Group judgements and the number of WCAs done is non-existent when controlling for deprivation (r=.047, p=.402) - if targets were having a large effect, I'd expect there to be a correlation; more WCAs done mean the assessors are more likely to reach the targets and have to start putting people into the WRAG instead of Support Group, so the proportion in the Support Group would go down. This isn't the case, as the relationship between the number of WCAs done and the proportion of judgements can be explained by local poverty - areas with more poverty do more WCAs as they have more ESA claimants.

The relationship between poverty and WCA outcome isn't accounted for by the total number of WCAs done, however. Together, this is evidence against the hypothesis that the observed bias is caused by targets or "norms".