The wrong side of the tracks: Starting school in a socially disadvantaged London borough

Abstract

Substantial evidence exists that social circumstances can affect children’s language development. As a result many children in socially deprived areas start school with delayed language, which may persist and adversely affect their attainment. We assessed the language of children in seven reception classes in a London (UK) borough and followed the progress of children with English as their first language (E1L) and with English as an additional language (EAL) during their first 2 years at school. Significant differences were found between schools. The effect of social factors on performance was reflected in a high correlation between the mean language score for each school and the percentage of children in the school receiving the pupil premium. Many of the children with EAL had very low scores reflecting their limited exposure to English prior to starting school. Most of these children attended schools where children with E1L also had low scores increasing the demands on the schools and their teachers. Children who had low initial scores made modest but significant progress during their reception year but failed to improve further during year 1 despite having non-verbal ability appropriate for their age. These results support previous findings that social deprivation can seriously delay language development, and that many children start school with weak communication skills. They add to previous findings by showing that the level of delay may differ substantially across schools in the same borough, by reporting data on children with EAL and by showing that children struggle to improve their abilities in the first 2 years of school.

Keywords

assessment English as an additional language language delay social disadvantage starting school

I Introduction

Many children living in socially deprived areas of the UK begin school with poorly developed language abilities. Locke et al. (2002) assessed children in four nursery schools in socially deprived areas of Sheffield with the Pre-School CELF (Clinical Evaluation of Language Fundamentals; Semel et al., 2006). Of 240 children, 55.6% were more than one standard deviation below the mean for their age, and 9.4% had severe delays with scores more than two standard deviations below their expected mean. The children’s non-verbal ability, though also below the expected level, was significantly better than their verbal ability. Locke and Ginsborg (2003) retested the children 2 years later. The percentage of children with mild delays decreased slightly, but the percentage of those with severe delays increased to 25.6% showing that attendance at school was failing to benefit their language. These findings were replicated by Law et al. (2011) who assessed primary school children aged between 5 and 12 years in a socially disadvantaged area of Scotland. The children’s mean score was close to one standard deviation below the score for their age and was lower than their non-verbal mean. Children with low scores were present throughout the age range tested again suggesting that attending school had failed to improve their ability.

The relationship between social deprivation and language delay is well established and substantially supported in the literature. Hart and Risley (1995) recorded verbal interactions of families with young children. Three-year-old children of professional parents had larger vocabularies than children of working-class parents and knew more than twice as many words as children of families receiving welfare. The quantity of language and style of interaction used by parents with their children differed. Professional parents used a conversational style, and working-class parents used a more directive style.

Subsequent studies have substantiated these findings. Cohort studies have shown the long-term effects of deprivation and detected variables that may counter these effects. Feinstein (2003) used data from the British Cohort study of 1970. Assessments at 22 months of age differed with socioeconomic status and predicted educational achievement at 26 years of age. Using data from the millennium cohort study, Blanden and Machin (2010) found that the vocabulary of children from families in the top fifth of incomes were more than a year ahead of those in the bottom fifth by age 5. Studies show that even short periods of poverty early in a child’s life can be as harmful for their development as persistent poverty (Dickerson and Popli, 2012; Holmes and Kiernan, 2013; Kiernan and Mensah, 2009, 2011). This early vulnerability confirms the importance of early experience on language and is consistent with the need for early intervention. The long-term advantages achieved by interventions such as the Perry High Scope programme (Schweinhart et al., 2005) have encouraged publically funded interventions in the US (Head Start) and the UK (Sure Start). These programmes recognized the harmful effects of existing levels of social deprivation. The initiation of Sure Start in the UK in 1998 formed a part of a government attempt to reduce poverty and social exclusion. A period of economic growth and provision of more generous benefits to poor families led to a decline in the numbers of children living in poverty, a trend which culminated in the passing of the Child Poverty Act 2010 which set a target that less than 10% of children would be in poverty by 2020.

Children’s home life and quality of parenting offer some protection against social deprivation. Holmes and Kiernan (2013) found that cognitive outcomes improved where mothers read regularly to a child, interacted positively with them and felt in control of their lives. Participation in Sure Start increased mothers’ life satisfaction and allowed them to provide a more stable and stimulating home background (National Evaluation of Sure Start, 2010, 2012).

These findings are for children with English as their first language (E1L). Minority ethnic groups are overrepresented in lowest quintile of socio-economic status (Dearden and Sibieta, 2010), and many children with English as an additional language (EAL) attend schools in socially deprived areas. Sylva et al. (2008) state that the impact of EAL on children’s English is much reduced by age 7 years compared to ages 3 and 5 years. However the children they studied had attended pre-school education so their ‘much reduced’ disadvantage may only follow after 3–4 years of exposure to English. Mahon and Crutchley (2006) found 4–9-year-old children with EAL were significantly behind on the British Picture Vocabulary Test (Dunn et al., 1997). The gap narrowed with age but remained in the oldest children. Two studies (Burgoyne et al., 2009; Hutchison et al., 2003) have shown effects of EAL on subsequent attainment. In both studies children aged between 6 and 8 years were behind in comprehending spoken and written texts. The latter deficit existed despite their having similar ability in phonics as children with E1L. Their comprehension failure was due to poor vocabulary knowledge and persisted across the age range of the children tested. These results recall the distinction made by Cummins (2008) of Basic Interpersonal Communication Skills (BICS) and Cognitive Academic Language Proficiency (CALP) and his view that these are acquired at different rates by children with EAL. BICS allows peer appropriate conversational ability and is usually reached after 2 years of exposure. In contrast CALP, which is required for academic attainment, may take from 5 to 7 years.

An analysis of the National Pupil Database by Strand et al. (2015) found that children with EAL are behind children with E1L at the end of the reception year (age 5) but that this disadvantage decreases at subsequent assessments and the percentage obtaining 5 GCSEs (national examinations taken at age 16 in the UK) differs by only 2.6 per cent. This finding needs some qualification however. Children with EAL on the database include all those exposed to a language other than English. For some, English may be their main language (or only language where another exists only as part of a family’s cultural heritage). Inclusion of these children in the comparison above will reduce the difference between the groups. Strand and Demie (2005) found that children with EAL who are fluent in English do significantly better than monolingual English speakers, and children with EAL who are not fluent do significantly worse. Strand et al. also found that the differences in attainment between children with E1L and with EAL were greater in some ethnic groups than others.

These results present a challenge to speech and language therapy services. Conventional forms of service delivery by referral and individual therapy are unlikely to be practical, and adoption of a ‘public health’ model has been suggested (Law et al., 2011). This approach will be difficult for services in socially deprived areas. The Bercow review of services for children and young people with speech language and communication needs (Department for Children, Schools and Families, 2008) found that more therapists were employed in these areas but with substantial variation among services with similar needs. Pring (2016) also found substantial variation among boroughs with high levels of deprivation in London.

We assessed children in reception classes in schools in a London borough. The borough is one of the most deprived local authorities in England and a majority of children starting school are from homes where English is not the first language. Despite the overall level of deprivation the borough is diverse containing areas of high deprivation and comparative affluence. Our aims in the research were:

to assess the English language skills of children with E1L and of children with EAL as they started school;

to compare the schools and to discover whether differences in the character of their catchment areas influenced the children’s scores; and

to assess the progress made by children with low scores (E1L and EAL) in their first 2 years at school and to compare their verbal and non-verbal abilities.

II Method

The study assessed children starting school in a London borough in 2012. The borough is the 13th most deprived of 326 local authorities in England (English Indices of Deprivation, 2010). The Marmot Review (Marmot, 2010) found that only 41.9% of children achieved a satisfactory level of development at age 5, the lowest of any local authority in England. It is the most socially diverse of London boroughs. Four of its wards are in the richest 10% in the country; five are in the poorest 10%. In the most deprived ward 44% of children live in poverty, in the least deprived only 5% do (London’s Poverty Profile, 2014). As our title suggests, areas of high and low deprivation are separated by a main railway line.

Seven schools within the borough were randomly selected, and a randomly selected reception class in each was assessed on the core sub tests (word structure, sentence structure and expressive vocabulary) of the CELF-Preschool 2 UK (Semel et al., 2006). The CELF Preschool 2 is standardized on English speakers allowing their scores to be converted into percentile scores. Normally it would not be used to assess children with EAL since it cannot give an indication of their general language ability. Here it was used to assess the adequacy of the children’s English relative to children with E1L and to allow us to monitor their acquisition of English over time. All children in each class were assessed subject to availability and parental consent. Testing took place in November 2012 when the children had been attending school for 2 months.

Two sub groups of children with low scores were retested at the end of their reception year and again at the end of year 1 to assess their progress. The first contained children with EAL whose scores placed them below the 25th percentile for English speakers. The second contained Children with E1L with scores below the 50th percentile. We anticipated that both groups would improve: the former because they were now consistently exposed to English in their classrooms, and the latter because their initial scores may have been reduced by social disadvantage. These children were also assessed on the pattern construction subtest of the British Ability Scales (Elliott et al., 1997) to assess their non-verbal ability.

All testing took place in a quiet room within the children’s schools and lasted approximately 20 minutes. It was conducted by a number of speech and language therapists. Children who were followed until the end of year 1 were tested three times, on each occasion by a different therapist. Ethical consent for the research was given by City University, London, and parental consent was obtained by the local speech and language therapy service.

III Results

One hundred and eighty-seven children were assessed. Seven children were not tested because of absences and two because parents did not give consent. Eighty-one were E1L, 106 (56.7%) were EAL. The latter spoke 34 different first languages. The percentage of children with EAL in the borough is 52.8%.

Table 1 gives the number of E1L and EAL speakers in each of the schools and their mean percentile score. The final column gives the overall mean percentile score for the children in each school. The schools differ widely in the balance of children with E1L and children with EAL. School 1 located in the affluent part of the borough has the highest overall score, high-scoring children with E1L and the fewest children with EAL. Schools 3–7 appear similar in general character, having substantial numbers of children with EAL who mainly have low scores and children with E1L also with below average scores. School 2 has the most diverse classroom with high-scoring children with E1L and low-scoring children with EAL.

Table 1.

Numbers of children with E1L and children with EAL and their mean percentile scores on the CELF-preschool.

School	E1L	Mean percentile score	EAL	Mean percentile score	Overall mean percentile score
1	24	60.12	3	40.33	57.92
2	17	61.42	12	10.08	40.17
3	12	48.25	12	25.83	37.04
4	13	39.46	12	8.20	24.46
5	6	38.00	24	19.79	23.43
6	8	33.25	17	14.21	20.60
7	1	50.00	26	16.07	17.33
All	81	50.90	106	16.91	31.63

Notes. CELF = Clinical Evaluation of Language Fundamentals; EAL = English as an additional language; E1L = English as their first language.

The overall mean percentile scores for the schools were broadly consistent with their location within the borough. To assess this more rigorously we examined the relationship between the children’s mean percentile score in each school and the percentage of children for whom the school received the pupil premium. The pupil premium is a payment made to schools for each socially disadvantaged child; the main criterion is that the child is eligible to receive free school meals. A significant inverse correlation was obtained (r(5) = −0.84, p = .01), showing a strong association between a high level of pupil premium and a low mean language scores in the schools. This correlation might arise if children with EAL with low scores are also the main source of pupil premium. However, a similar correlation was obtained when only the children with E1L were analysed (r(5) = −0.86, p < .01).

A one-factor ANOVA found a significant difference between the overall mean percentile scores for the schools (F(6, 173) = 2.36, p < .05). This comparison is heavily influenced by the numbers of low-scoring children with EAL in the schools. Differences also existed between schools when only children with E1L were considered. Their overall mean was 50.9%, close to the expected score for a randomly selected group of children. The schools differ significantly (F(6, 81) = 2.28, p <.05). Table 2 shows that children with E1L divide almost equally between the two high-scoring schools (41) and the five lower scoring schools (40). One-sample t tests showed that children in the low-scoring schools were significantly below the mean (t(39) = 2.57, p < .01) and that those in the two high-scoring schools were significantly above the mean (t(40) = 1.77, p < .05).

Table 2.

Mean percentile scores on CELF-preschool for high and low-scoring children with E1L by schools.

Schools	n	Mean percentile score	Standard deviation
1 and 2	41	60.66	26.38
3–7	40	40.90	24.37

Notes. CELF = Clinical Evaluation of Language Fundamentals; E1L = English as their first language.

A two-factor between participants ANOVA examined differences associated with gender and language status. Significant effects of gender (F(1, 183) = 9.90, p < .01) and language status (F(1, 183) = 85.62, p < .001) were found. Table 3 shows that girls and children with E1L had higher scores. The advantage for girls appears particularly marked in the EAL group. However, the interaction between gender and language status was not significant.

Table 3.

CELF-preschool mean percentile scores by gender and language group.

Language	Gender	n	Mean percentile score	Standard deviation
E1L	girls	46	54.61	23.36
	boys	35	46.03	31.09
EAL	girls	47	24.49	24.62
	boys	59	10.87	17.37

Notes. EAL = English as an additional language; E1L = English as their first language.

Thirty-seven children with E1L (45.7 %) had scores below the mean for their age. As Table 2 shows most of these children attended schools in the deprived parts of the borough. Eighty-three children with EAL (78%) had scores below the 25th percentile for English speakers, and 51 of these (48%) were within the bottom 5% for English speakers. The progress of these two groups was followed during their first 2 years in school. At issue here is whether attendance at school benefits in the former case children whose language may have been delayed by social deprivation, and in the latter children who are learning English.

As there was attrition over time (14 children were unavailable at the end of reception and a further 6 at the end of year 1) we report the progress of the children in two stages: first at the end of their reception year, and then at the end of year 1. Table 4 gives the percentile scores of children at the end of their reception year.

Table 4.

Mean percentile scores of low-scoring children at the initial assessment and at the end of reception year.

	N	CELF Nov 2012: Mean percentile (standard deviation)	CELF July 2013: Mean percentile (standard deviation)	Nonverbal July 2013: Mean percentile (standard deviation)
EAL	74	7.48 (9.63)	16.95 (22.94)	53.42 (22.51)
Girls	26	11.15 (11.99)	25.55 (23.62)	61.11 (21.37)
Boys	48	5.48 (7.49)	12.29 (12.19)	49.25 (22.21)
E1L	32	23.12 (15.74)	36.78 (24.39)	50.53 (25.19)
Girls	15	27.53 (14.28)	44.93 (23.95)	60.00 (19.75)
Boys	17	19.23 (16.35)	29.59 (23.09)	42.17 (27.02)

Notes. CELF = Clinical Evaluation of Language Fundamentals; EAL = English as an additional language; E1L = English as their first language.

Both groups improved significantly (EAL t(73) = 5.98 p < .001; E1L t(31) = 4.39, p < .001) during their reception year, although the scores at the end of the year remain low particularly so for the children with EAL. The weakness of language scores is emphasized by the percentile scores on the pattern construction test in which both groups performed normally. As in the overall analysis, girls outperformed boys (F(1, 104) =14.31 p < .001) and also made significantly greater improvement (F(1, 104) = 7.17, p < .01). They also had higher non-verbal scores than boys (t(104) = 2.97, p < .01).

Table 5 gives the scores of children retested at the end of year 1. These results are a marked contrast with those at the end of the reception year. Here, the progress made by children with EAL was slight and not significant, and the scores of children with E1L had declined significantly (t(30) = 2.49, p < .05). In general the effects of year 1 at school appear to have slowed the children’s progress. Girls continued to out-score boys but whereas they had previously progressed significantly faster they are now marking time.

Table 5.

Mean percentile scores of low-scoring children at initial assessment, at end of reception year and at end of year 1.

	n	CELF Nov 2012: Mean percentile (standard deviation)	CELF July 2013: Mean percentile (standard deviation)	CELF July 2014: Mean percentile (standard deviation)	Nonverbal July 2104: Mean percentile (standard deviation)
EAL	69	7.37 (9.10)	17.59 (18.25)	21.44 (22.97)	52.34 (21.44)
Girls	25	11.56 (12.06)	26.56 (23.54)	27.80 (26.93)	59.60 (20.34)
Boys	44	5.48 (7.49)	12.29 (12.19)	17.82 (19.82)	48.22 (21.17)
English	31	23.84 (15.46)	37.93 (24.39)	33.09 (24.03)	51.64 (24.79)
Girls	15	27.53 (14.28)	44.93 (23.95)	41.13 (25.13)	60.00 (19.75)
Boys	16	20.37 (16.17)	31.37 (22.60)	25.56 (20.98)	43.81 (27.02)

We investigated whether the children’s progress differed across schools. The scores of children with E1L and with EAL were combined in this analysis to increase the numbers of children in each school. School 1 (see Table 1) was excluded as only 6 children were followed through to year 1. A two-factor mixed ANOVA found a highly significant interaction between school and time of assessment (F(10, 83) = 3.53, p < .001). Table 6 shows that school 3 had the strongest gains in reception and continued to improve in year 1 when other schools remained static or fell back. These results should be treated cautiously due to the relatively small numbers of children per school (13–19). Nevertheless, they suggest that there are differences between schools in the way they seek to help children with poor English language abilities.

Table 6.

Progress of low-scoring children until the end of year 1 (mean percentile scores on CELF-preschool).

School	Number of children	CELF Nov 2012: Mean percentile	CELF July 2013: Mean percentile	CELF July 2014: Mean percentile
2	14	7.28	21.03	28.21
3	13	18.69	36.15	48.84
4	16	17.03	25.68	19.50
5	19	9.31	15.95	16.06
6	15	11.33	26.73	20.35
7	17	6.11	12.02	16.47

IV Discussion

These results confirm previous findings (Law et al., 2011; Locke et al., 2002) that children starting school in socially deprived areas have weak English language skills. They are also consistent with the recent report from the Institute of Health Equity (2014) that only 51.7% of children nationally gained a good level of development after completing their reception year at school and with the UK’s poor ranking for education on UNICEF’s (2013) assessment of child well-being.

Disproportionate numbers of children with EAL are found in many socially deprived areas. Our results highlight both the extent of the problems facing some schools and the differences that can exist between schools in the same borough. They emphasize the differing levels of need of the children within the schools and the differing demands placed upon teachers and other professionals who work with them. For several of the schools tested the combined effects of social deprivation and lack of exposure to English mean that a majority of children in a class may be performing well below their nationally expected levels. In this environment it may be difficult for children to catch up or for teachers to accurately assess the level of need of individual children. As children progress in school and face other competing demands it may become increasingly difficult to offer the help they need to improve their communication skills.

It is important to state that we do not attribute blame to the schools for the poor language abilities of the children. When first tested the children had little chance to progress having been at school for only 2 months. To our observation the schools provided a stimulating and encouraging environment and the great majority of the children were happy and enthusiastic. These observations were supported by good and outstanding Ofsted reports (published following statutory inspection visits to schools by the Office for Standards in Education, Children’s Services and Skills, UK).

The slow improvement of the children during their first 2 years at school is as alarming as their initial poor levels of English. Here we followed children with low initial scores: children with E1L below the mean for their age and more than three quarters of the children with EAL, all below the 25th percentile for English speakers. Both groups were otherwise unselected; both groups may include a few children with additional problems affecting their language development. Nevertheless, the mean scores on the pattern construction test suggest that both groups had a normal range of non-verbal abilities. Both groups made modest but significant gains during their reception year but failed to progress in year 1. It appears that year 1 classes and the greater demands they place on children is less conducive to their language development. As a result the competence of both groups of children in English after 2 years at school was far below that expected for their ability. Their scores are particularly alarming given that, by selecting the lowest scoring children some purely statistical improvement might have been expected due to regression to the mean.

Children in one school appeared to be an exception to this finding. They improved more strongly in their reception year and further progress in year 1 took them close to their expected level of language ability. The small numbers of children in this comparison suggests caution in interpreting this finding. Nor do we have information about the methods used in the individual schools that might explain the differences in the children’s progress. Strand et al. (2015) also detected differences in children’s progress across schools but were unable to find a common underlying cause of these differences. Nevertheless the possibility that some school environments are more beneficial for these children than others merits further investigation.

Learning objectives in year 1 include a strong emphasis on phonics as an essential part of acquiring literacy. That children with EAL will find this progression difficult is borne out by the findings of Hutchison et al (2003) and Burgoyne et al (2009) that they are able to acquire good decoding skills but have poor reading comprehension. Mahon and Crutchley (2006) also found that children with EAL remained behind their peers at 9 years of age on single word comprehension, a task that makes relatively low demands on their understanding.

There were strong effects of gender in our data. Girls had significantly higher scores overall and made better progress than boys during their reception year. The large gender difference in the initial scores of the children with EAL is notable. If their limited exposure to English is the cause of their low scores, then it appears that girls require less input than boys to acquire the language.

Although we have only followed children with EAL over the first 2 years of school, their lack of progress in English appears inconsistent with research showing that their eventual attainment is comparable with children who are monolingual English speakers. Although a few of the children with EAL we assessed had scores within the normal range, the great majority had very low scores, which suggest that they are from homes where little English is spoken. They may not be comparable with the national sample on which Strand et al. (2015) reported, which included children who although exposed to other languages may be proficient in English. Moreover, many of the children came from ethnic groups (black African and white other with EAL), which do less well in improving their English and in school attainment (Strand et al., 2015).

The scale of the problems presented by children from socially deprived areas and by children with non-English home languages is likely to exceed the resources available to help them. Law et al. (2011) have suggested that a public health approach is required. What form this approach should take is unclear. Early intervention in the pre-school and early school years is important, and the awareness of carers and teachers in these contexts should be raised. The UK Government is aware of the need for early intervention (see, for example, Allen, 2011) and of the relationship between social disadvantage and speech, language and communication needs (All Party Parliamentary Group on Speech and Language Difficulties, 2013). Two interventions – in particular, the Sure Start programme and the introduction of the pupil premium –have targeted children from disadvantaged homes. Evaluation of Sure Start (National Evaluation of Sure Start, 2010, 2012) has shown positive effects on the parents involved and on their behaviour towards and encouragement of their children, but direct effects on the children’s cognitive outcomes are unclear. The pupil premium introduced in 2011 gives schools extra funding initially set at £430 per child eligible for free school meals but subsequently increased to £1320 for primary schools (Jarrett et al., 2015). Not all of this money is new since it replaced other sources of funding previously available to schools (see Lupton and Thomson, 2015; Lupton et al., 2016), but the latter figure appears generous, and as those authors point out a merit of the system is that it is redistributive, increasing funding in schools in more deprived areas and drawing attention within those schools to the needs of children with social deprivation. Schools may choose how the money is spent (although they must report this on their web sites, and the spending is examined by Ofsted). Schools are encouraged to use the Educational Endowment Foundation’s findings on what methods benefit children, and nearly two thirds report doing so (National Audit Office, 2015).

Given the close relationship between children’s language and the level of pupil premium in their schools, a strong case can be made for using the resulting funds to improve their communication skills. Speech and language therapy despite limited resources has an important role here given its expertise in language development and remediation. Some interventions have shown promise. At the pre-school level parents can be trained to improve their interactions with their children (Buschmann et al., 2009; Falkus et al., 2016; Van Balkom et al., 2010), and interventions within schools have been shown to improve the language skills of children with E1L and children with EAL (Dockrell et al., 2010; Lee and Pring, 2016; Fricke et al., 2013). Further research in this area, particularly with children who are socially disadvantaged and children with EAL, is needed.

The association between social deprivation and language suggests that poverty is an important influence on language development. In 2010 when the Child Poverty Act was passed, 17.5% of children (2.25 million children) in the UK were living in poverty (households with incomes below 60% of median income). This figure was a result of a slow decline over the previous decade driven substantially by the provision of benefits and tax credits to families with children. The reversal of this policy has seen poorer families disproportionately affected by cuts to benefits (Browne and Elming, 2015; De Agostini et al., 2014) as well as suffering from stagnant or declining levels of real incomes (Office of National Statistics, 2014). Cuts to local authority budgets have meant that spending on early years services (early education, child care and Sure Start) have fallen in real terms by 25% (Stewart and Obolenskaya, 2015). In 2015–16, the number of children in poverty had increased only slightly to 17.8%, but was predicted to increase more sharply in the coming years, reaching 25.7% by 2020 (nearly 3.5 million children) (Browne and Hood, 2016).

These conditions are likely to result in financial stress for families. The extent of the social changes that have resulted is disputed; for some the number of households with precarious financial circumstances constitute a new social class ‘the precariat’ (Savage et al., 2015; Standing, 2014). Objectively they are reflected in the fact that more than half of children and working age adults in poverty are in working households (Aldridge et al., 2012). Given the evidence that even short periods of poverty early in life can affect children’s language development, the present economic climate might be thought designed to achieve this. While interventions can help children, the extent of the problem can only realistically be addressed by changes in economic and social circumstances.

Footnotes

Declaration of conflicting interest

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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