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ORIGINAL PAPER
Preference Organization and Cross-Cultural Variationin Request Responses: A Corpus-Based Comparisonof British and American English
Ilka Flock1 • Ronald Geluykens1
Received: 29 November 2016 / Accepted: 14 July 2017 / Published online: 2 August 2017
� Springer International Publishing AG 2017
Abstract This study compares request responses in two national varieties of
English, American English (AmE) and British English. The responses are manually
retrieved from two corpora of English, the British component to the International
Corpus of English and the Santa Barbara Corpus of Spoken American English and
analyzed both for their function and format. It is shown that request responses in
both varieties pattern as preference structure would predict: compliant responses
occur more frequently than non-compliant ones and can thus be understood as the
preferred response type to requestive first pair parts. The analysis of co-occurrence
patterns of first and second pair parts reveals that the directness level of the first pair
part does not significantly influence the response type of the second pair part. It
does, however, have an impact on the level of explicitness of the response. While
cross-cultural differences in request responses are generally rare in the present
database, they do surface in the higher numbers for implicit compliance in the AmE
corpus. These results show the importance of a cross-cultural approach to the study
of naturally occurring request responses retrieved from corpora of authentic speech.
Keywords Request responses � Preference organization � American
English � British English � Pragmatic variation
Introduction
The present paper is a corpus-based contrastive investigation into verbal responses
to requests in two national varieties of English: American English (AmE) and
British English (BrE). With this research design, we aim at combining two research
& Ilka Flock
1 Department of English and American Studies, University of Oldenburg, Ammerlaender Heerstr.
114-118, 26129 Oldenburg, Germany
123
Corpus Pragmatics (2018) 2:57–82
https://doi.org/10.1007/s41701-017-0022-y
traditions which have mostly been carried out separately from each other. Firstly,
while cross-cultural pragmatics (CCP) has investigated (and indeed found) regional
and social differences in language use, it has focused heavily on first pair parts of
adjacency pairs. This focus has (at least partially) been caused by the omnipresence
of discourse completion task (DCT) data, which makes it almost impossible to study
interactional aspects of language use. Secondly, the conversation analytic tradition,
has, conversely, provided us with many insights on the sequential aspects of
conversation, but has generally not included a cross-cultural perspective; neither has
it attempted a quantitative evaluation nor a comparative perspective.
What we know about request sequences thus stems from studies which either (1)make
use of data with questionable validity (DCT-based CCP) or (2) have offered accounts
based on naturally occurring data which avoid cross-cultural comparisons altogether. The
present study is an attempt to fill this research gap by employing a corpus-based
contrastive approach. We rely on the conversational data retrieved from two corpora of
English to obtain a database of request sequences large enough for both quantitative and
qualitative analysis. Our objective is to answer the following research questions:
1. How are request responses realized functionally (in terms of preference
organization) and formally (both in terms of explicitness and in lexico-
grammatical terms) in naturally occurring conversations?
2. Is there a correlation between request and response, i.e. the realization of the
second pair part contingent on the directness of the first pair part?
3. Do systematic cross-cultural differences occur between AmE and BrE request
responses (from both a formal and functional point of view)?
We will first provide the reader with a short definition of requests and their
responses, before reviewing studies investigating naturally occurring requests and
their responses (see ‘‘Empirical Studies on Requests and Their Responses’’ section).
We will then briefly outline the data collection procedure and justify the choice of
corpora and their comparability (see ‘‘Methodology ’’ section) before discussing our
results in detail (see ‘‘Results’’ section).
Empirical Studies on Requests and Their Responses
Requests and Request Responses
According to classic speech act theory, requests are defined as directive speech acts
in which a speaker wants the hearer to do a future action which they would not have
done without the production of the request (Searle 1976). While Austin’s (1962)
original conceptualization of speech acts entails an interactive perspective (in that
the illocutionary act has three effects including the production of an uptake and
inviting of a response), Searle’s (1969) account of speech acts developed into a
cognitive theory of speaker meaning. As a consequence, the interactional dimension
of speech acts has been overlooked (cf. Sbisa 2013). The assumption that pragmatic
meaning is created predominantly by the speaker is taken up by speech-act based
58 I. Flock, R. Geluykens
123
approaches to verbal politeness. In Brown and Levinson’s (1987) theory, requests
are conceptualized as intrinsic face threatening acts which are likely to be realized
by indirect linguistic choices, including the use of politeness strategies.
As a result, both speech act theory and related theories of verbal politeness are
unable to account for the interactional properties of requests. Thus, different
explanatory frameworks, such as conversation analysis, need to be invoked.
Conversation analysis (CA) has its roots in ethnomethodology and assumes that
language is a social practice (Schegloff 1996; Drew and Curl 2008; Heritage 2008).
From a conversation analytic perspective, requests are prototypically viewed as first
pair parts of an adjacency pair which create the expectation of a second pair part
(response) to occur (Schegloff 1972; Schegloff and Sacks 1973). Yet not all
alternative second pair parts are equal in status; some might be preferred while
others are dispreferred. Dispreferred second pair parts prototypically display
structural markers of dispreference such as delays, qualifications and accounts
(Pomerantz 1984; Levinson 1983; Walker 2013). Research on requests and their
responses has shown unequivocally that indications of non-compliance are
dispreferred second pair parts while indications of compliance are preferred
(Levinson 1983; Davidson 1984; Lee 2011). Furthermore, the production of a
second pair part can be an indicator that the addressee has understood (or failed to
understand) the speaker’s intention (Sacks et al. 1974; Hutchby and Wooffitt 2006;
Drew and Curl 2008). Second pair parts can thus serve as a monitoring device not
only for speakers to check whether their intentions were identified correctly but also
for researchers attempting to identify speech acts in authentic discourse.
Empirical Studies on Requests
While there is a wealth of request studies based on Discourse Completion Task
data,1 there are only a few studies on requests which employ naturally occurring
data. While there is some research based on parent–child interactions, institutional
discourse or service encounters (e.g. Wootton 1981, 1997; Craven and Potter 2010;
Pufahl Bax 1986; Vine 2009; Geluykens 2011; Felix-Brasdefer 2015) only three
studies observe adult speakers in informal contexts. The earliest and most influential
of these is Ervin-Tripp’s account of requests in (mostly) conversational American
English (AmE). The author establishes a taxonomy of six request types based on
formal, discursive, and social criteria. She distinguishes between need statements,
imperatives, embedded imperatives, permission requests, request questions and
hints which are used in different social situations and constellations. She reports that
almost all request types can be used in a variety of contextual situations.2
In a more CA oriented approach to the study of requests, Curl and Drew (2008)
compare requests in naturally occurring private telephone conversations to
requests in telephone calls to a primary care physician’s practice in Britain. While
1 For DCT-based studies on English cf. e.g. Blum-Kulka et al. (1989), Breuer and Geluykens (2007),
Barron (2008).2 The request taxonomy introduced by Ervin-Tripp (1976) is also used in Goldschmidt’s (1998) account
of what she calls ‘favor asking’ sequences in American English.
Preference Organization and Cross-Cultural Variation… 59
123
their approach generally is a qualitative one, the authors report that two thirds of
the requests in their conversational corpus are realized by modal verbs which
either question or state the hearer’s ability or willingness to comply with the
request (can/could/will) or imperatives. The authors find a different pattern of
requesting in the institutional corpus (with modal expressions being almost absent
and requests prefaced with I wonder being frequent) and conclude that speakers
use the different request formats to ‘‘display or claim entitlement to make a
request, and to display (or conversely, not acknowledge) an understanding of the
contingencies associated with granting their request’’ (Curl and Drew 2008: 16).
They argue that the use of modal verbs indicates that speakers treat their request as
non-contingent in the sense that they ‘‘treat the conditions necessary for granting
their request as fulfilled, and therefore their request as unproblematic’’ (Curl and
Drew 2008: 27). In contrast, requests prefaced with I wonder if show the speaker’s
awareness of the contingencies associated with the granting of the request. The
authors conclude that by choosing a particular request format, speakers ‘‘make a
claim as to what they believe themselves reasonably entitled to’’ (Curl and Drew
2008: 27) and thus display their social relationships through the use of certain
language forms.
In a contrastive study comparing request for non-verbal action in American and
British English (BrE) conversational data, Flock (2016) also finds that imperatives
and modal constructions which either question or state the hearer’s ability or
willingness (‘preparatory’) constitute the most frequent request realization strategies
for compliance. In her conversational data, imperative-based requests and elliptical
structures (‘mood derivables’) alone account for 49.6% of all requests in the AmE
and 39.6% in the BrE database (Table 1; cf. Flock 2016: 121).
Similar to Curl and Drew (2008), modal constructions (‘‘preparatory’’) also
belong to the most frequently employed requesting strategies. However, they occur
with markedly lower frequencies than the imperative strategies (20.4% of all
requests in AmE and 25.0% in BrE).
Table 1 Request strategies and directness levels in conversational requests
Directness level Head act strategy Example AmE BrE
N % N %
1 Mood derivable Do X 129 49.6 103 39.6
Obligation statement You should/must do X 31 11.9 43 16.5
2 Performative I request/ask you to do X 1 0.4 4 1.5
Want/need statement I want/need you to do X 7 2.7 3 1.2
Preparatory Can you do X? 53 20.4 65 25.0
Suggestory formula How about doing X? 28 10.8 26 10.0
3 Hint No codified form 11 4.2 16 6.2
Total 260 100.0 260 100.0
60 I. Flock, R. Geluykens
123
Empirical Studies on Request Responses
While the majority of research has been conducted on the first pair part, responses to
requests have attracted at least some attention from researchers working in different
paradigms. While some of these studies are more cognitive in nature (cf. e.g. Clark
1979; Clark and Schunk 1980), the ones that are most relevant to our purposes
investigate responses sequentially as adjacency pair second parts in a CA
framework. One of the few such response studies based on conversational non-
institutional data in English is Rauniomaa and Keisanen (2012), who analyze
requests and responses in naturally occurring casual conversations. They report that
out of 69 request sequences they analyze, 56 are complied with and focus on this
type of responses in their analysis. They report on two different multimodal formats
of request responses. The first format consists of the request’s fulfilment only
(without there being a verbal response). The vast majority of all favorable responses
in their corpus follows this structure. The second format consists of two
components, an acceptance (affirmative response token) and the actual fulfilment
of the request. The authors report that, as some requests cannot be fulfilled
immediately, the affirmative response tokens might indicate future rather than
immediate compliance with the request.
Stivers and Rossano (2010) also investigate responses to requests from a CA
perspective but focus on the relation between first and second pair part. They find
that different first pair parts mobilize responses to different degrees. Their analysis
shows that off-record request strategies are less likely to evoke a response by the
addressee than more direct strategies. The authors invoke Brown and Levinson’s
(1987) concept of a priori payoffs for off-record language use. They claim that
speakers who use off-record request strategies are not only ‘‘less coercive of a
particular type of response, but they are also less coercive of any response’’ Stivers
and Rossano 2010: 26; original emphasis). Consequently, they conclude that the
indirect nature of the off-record request has a lower mobilization potential than
more direct first pair parts. This claim, however, still needs further investigation
since the authors do not quantify their results and only present isolated examples as
evidence.
Thompson et al.’s (2015) study contains the most elaborate account of request
responses in naturally occurring conversation to date. The authors analyze responses
in AmE request-for-action sequences and develop a taxonomy of response forms for
request sequences. The authors distinguish between five different responsive actions
in request-for-action sequences: (1) particle, (2) minimal clausal, (3) expanded
clausal, (4) graded clausal and (5) unrelated clausal. The different responsive
actions are distinguished from each other on formal grounds and differ in their
degree of autonomy from the first pair part, the degree of the requestee’s
accountability, and assumed agency (Table 2 gives an overview). While particle
responses display the lowest degree of turn autonomy, unrelated clausal responses
are (as the name suggests) completely unrelated to the prior request grammatically
and thus display the highest degree of turn autonomy.
The authors dismiss both preference-organizational and minimization accounts as
explanatory models for the relation between request and response, as both accounts
Preference Organization and Cross-Cultural Variation… 61
123
are unable to explain the relatively high numbers for elaborate compliance
responses in their AmE data. Instead, they employ a deontic rights approach to
explain how first and second pair part are related. They operationalize deontic rights
by invoking the concepts of entitlement and contingency (cf. also Lindstrom 2005;
Heinemann 2006; Curl and Drew 2008; Craven and Potter 2010). While entitlement
refers to how speakers position themselves with respect to having the right to make
their addressee do an action, contingency relates to the requester’s awareness of the
possibility that there may be factors which prevent the request from being complied
with. Thompson et al. (2015) maintain that strong claims to deontic rights translate
into a high display of entitlement and a low display of contingency. In turn, weak
claims to deontic rights correspond to a low display of entitlement and a high
display of contingency. Following Stevanovic and Perakyla (2012), Thompson et al.
(2015) suggest that participants in conversation strive to achieve a situation of
deontic congruence in which a requester’s strong deontic rights are met with a
display of weak deontic rights on the part of the requestee. As the authors relate the
display of agency in responding to requests to a display of strong deontic rights, the
response forms identified can be correlated with the pattern established. As particle
responses display the lowest degree of agency, they also display the weakest claim
to deontic rights and are thus the prime candidates for responding to a request with
high display of deontic rights. Unrelated clausal forms, with their high display of
agency and thus strong deontic rights, should then be expected to occur after
requests displaying weak deontic rights (cf. Table 2; dark hue indicates strong
realization of a criterion).
When it comes to the frequency distribution of the different response strategies,
Thompson et al. (2015) find that particle responses are overall the most frequent
Table 2 Requestive action forms (partly based on Thompson et al. 2015: 223–224)
Particle Minimal clausal Expanded clausal Graded clausal Unrelated
clausal
Linguistic
form
compliance
alright
okay
sure
I will, I’d be
happy to, etc.
I won’t
I’ll X
I won’t X
[X = requester’s
formulation of
action]
I’ll Y
I won’t Y
[Y = alternative
formulation of
action]
[preparatory
steps]
Linguistic
form non-
compliance
no I’m not
I don’t want/like
to, I like to,
etc.
I’m not Xing
will X, I am Xing
[X = requester’s
formulation of
action]
n.a. [reasons for
non-
compliance]
Turn
autonomy
Agency
Claim to
deontic
rights
62 I. Flock, R. Geluykens
123
responses (N = 40) followed by unrelated clausal responses (N = 27). Minimal
clausal (N = 12), expanded clausal (N = 10) and graded clausal responses (N = 7)
occur with markedly lower frequencies. In the two most frequent response types, a
clear functional contrast can be identified: Whereas particle responses are
predominantly used to signal compliance (36 compliance vs. 4 non-compliance
strategies), unrelated clausal responses are mainly used to express non-compliance
(9 compliance vs. 18 non-compliance strategies). For the other response types, the
patterns are either not as clear-cut or the numbers are too low for generalizations.
Flock’s (2016) study on naturally occurring data, finally, focuses primarily on the
analysis of requests (first pair part), but uses responses as an identification criterion
and offers a brief cross-cultural analysis of request responses in AmE and BrE. In
contrast to Rauniomaa and Keisanen (2012), she finds that out of the 520 requests
she analyzes, the majority are responded to verbally. With a focus on verbal
responses only, she distinguishes between two response formats (compliance vs.
non-compliance) and within each category between explicit and implicit responses,
adding up to four different permutations. Flock (2016) counts the production of
agreement with the literal meaning of the request (e.g. yeah or yes) and verbal
indications of compliance (e.g. I will) as explicit compliance strategies. Implicit
compliance is mostly realized by responding with a request for specification. While
explicit non-compliance includes disagreement (e.g. no) and verbal indications of
non-compliance (e.g. I won’t), implicit non-compliance is achieved by providing
reasons for the non-compliance, challenging the appropriateness of the requested
action or the requester’s entitlement for the production of the request. In a brief
cross-cultural analysis of request responses, she finds mild differences between
AmE and BrE responses in that BrE speakers tend to use more explicit compliance
strategies than their AmE counterparts. While the author does not include a
systematic formal analysis of request responses, her functional analytical categories,
in particular her distinction between explicit and implicit responses, also form the
basis for the present paper.
To summarize, studies based on naturally occurring data have provided us with
findings about the surface structures both requests and their responses can take. In
contrast to disciplines such as cross-cultural pragmatics, existing studies to date
have not studied request sequences from a contrastive perspective (with the
exception of Flock 2016). Thus, there is a regrettable lack of research on cross-
cultural differences in the realization of both naturally occurring requests and their
responses.
Methodology
Speech Acts and Corpus Linguistics
Corpus linguistic methodology originally was developed with the aim of electron-
ically accessing representative samples of linguistic forms in large language
databases. In contrast to most speech act studies, corpus linguistic research
prototypically takes a form-to-function perspective, where linguistic forms
Preference Organization and Cross-Cultural Variation… 63
123
constitute the starting point and can be used as search tokens for electronic searches.
However, as all studies on requests have shown, this speech act can take numerous
forms, ranging from realization strategies which are routinely associated with
certain linguistic forms (e.g. imperatives) to those which are not codified at all (e.g.
hints). Moreover, most of the forms realizing requests can also be employed to
encode intentions other than requesting. Automated searches run the risk of not
retrieving some requestive realizations while at the same time locating forms which
are used with different intentions. Consequently, in their study on compliments in
the British National Corpus (BNC), Jucker et al. claim that speech acts ‘‘are not
readily amenable to corpus-linguistic investigations’’ (2008: 273). In a review on the
use of corpora in pragmatics research, Ruhlemann (2010: 289) comes to the same
conclusion and adds that contextual information is only recorded ‘‘crudely’’ in
corpora.
Thus, all corpus-based studies on speech acts so far have limited themselves to
the investigation of their conventionalized or even formulaic linguistic realizations
and were thus able to use automated searches. Such studies have thus focused on
lexicalized stems of speech acts like apologies (Deutschmann 2006), suggestions
(Adolphs 2008) expressions of gratitude (Jautz 2008; Wong 2010) or the bathroom
formula (i.e. requests to leave an ongoing activity to go to the bathroom; Levin
2014). The authors acknowledge that while they were able to retrieve convention-
alized realizations of the speech acts, they had no means of locating non-
conventionalized strategies.
Despite the obstacles of automated corpus searches, we claim that corpora (or
more specifically, their textual basis) do have a major potential even for research on
non-conventionalized speech act realizations. As requests (like many other speech
acts) can be considered to be low frequency items, only large databases can provide
sufficient numbers for representative analyses. As a number of corpora have been
specifically compiled for contrastive analyses, they are also well suited for cross-
cultural pragmatic research. Corpus series like the International Corpus of English
(ICE)—a corpus project which aims at representing different varieties of English
and which is designed to facilitate contrastive corpus-based analyses between
them—spring to mind most readily.
However, the problems with automated searches and the need for large databases
in pragmatics research call for the development of pragmatically annotated corpora.
The only corpus with pragmatic annotation we are aware of is the Irish component
to ICE. The annotation system used (SPICE, Systems of Pragmatic Annotation in
the Spoken Component of ICE-Ireland) includes corpus mark-up for speech act
functions, utterance tags and discourse markers. The Searlean classification of
illocutionary types is used as the basis for speech act annotation (cf. Kallen and Kirk
2012; Kirk 2016). While this system may still not be sufficient for employing
automated searches for each pragmatic phenomenon, it provides a direction in
which pragmatic corpus annotation may develop. For the time being, researchers
interested in the study of non-codified pragmatic phenomena in varieties other than
Irish English (including the present authors) have to be content with manual
searches of corpus material.
64 I. Flock, R. Geluykens
123
Corpora Used and Coding Scheme
The database of the present paper consists of verbal responses to requests retrieved
from two corpora of spoken English in manual searches (what Kohnen 2008: 296
calls a ‘‘genre-specific micro-analytic bottom-up’’ approach). The request sequences
were identified not just by searching for the first pairs; rather, the interpretation of an
utterance by co-participants was taken into consideration. Only those sequences
were included in the present analysis where a verbal uptake was provided by a
participant that marks the first pair part as a request. Overall, 171 AmE and 201 BrE
request sequences with verbal responses were retrieved from the databases. Non-
verbal utterances (of the type frequently found by Rauniomaa and Keisanen 2012)
were not included in the analysis.
The AmE request responses were retrieved from a subcorpus of the Santa
Barbara Corpus of Spoken American English (SBCSAE) while the BrE data were
extracted from the conversational part of the British component to the International
Corpus of English (ICE-GB). Each component of ICE consists of 500 text samples
(300 spoken, 200 written) of 2000 words each, adding up to a total of one million
words. ICE-GB is not only POS-tagged but also parsed. Further annotation includes
the indication of overlap. The SBCSAE consists of 60 transcripts sampled with the
aim of providing a source for researchers ‘‘interested in the nature of spoken
American English, and more generally, of spoken language’’ (Chafe et al. 1991: 65)
in descriptive, theoretical or pedagogical contexts. The SBCSAE does not only offer
orthographic transcriptions of the data but also intonational mark-up, overlap and
pauses.
While there are larger and more up-to-date corpora available (such as the British
or American National Corpus or The Bank of English), the two corpora were chosen
for a number of reasons for the purposes of the present study. Unlike many other
corpora, ICE-GB and the SBCSAE provide researchers with a wealth of
demographic background information on speakers, enabling them to control for
many macro-social factors. This is a crucial prerequisite for pragmatics research as
it has become clear to researchers that many pragmatic phenomena are sensitive to
macro-social variation. As the two corpora (ICE and SBCSAE) are not per se
comparable when it comes to the discourse types included, subcorpora were
sampled to guarantee maximum comparability between the language samples
included (cf. Table 3). While only the private dialogue transcripts of ICE-GB were
chosen for analysis (N = 100), all transcripts containing scripted language material
(such as sermons or guided tours) were excluded from the SBCSAE.
With the help of the demographic information provided, the subcorpora sampled
are kept comparable not only for discourse type included but also for macro- and
micro social factors. Overall, the subcorpora are balanced for gender, age, ethnicity
and educational level of the speakers and include conversations with equal power
and low social distance speaker constellations.3 Overall, we can thus conclude that
3 See Flock (2016) for a more thorough description of the database. As the current database of responses
stems from the same subcorpora, the information given there also apply to the present study.
Preference Organization and Cross-Cultural Variation… 65
123
the databases are comparable and that any pragmatic variation found must be due to
cross-cultural variation.
The coding scheme employed in the present study is based on the analytical
categories established in previous studies in request responses. More specifically,
we have incorporated the analytical categories used in Flock (2016) and
supplemented them with the formal response categories established in Thompson
et al. (2015). We thus distinguish between two response types (compliance vs. non-
compliance) which each include two categories (explicit vs. implicit). Within these
categories, we further distinguish between different response strategies which can
then, in turn, be classified according to the formats that Thompson et al. have
reported. Table 4 provides an overview of our coding scheme and gives an example
for each category used in our database.
Statistical Analysis
For the statistical analysis we used Generalized Linear Mixed Effects Models
(GLMMs). We used the RStudio 1.0.136 (RStudio Team 2015) built on the R
software (R Core Team 2013, version 3.3.2) and the R package ‘‘lme4’’ (Version
1.1.12) with the function ‘‘glmer’’ to perform GLMMs on our data to model both
participant- and item-variability (Bates et al. 2015). GLMMs allow for differences
between participants and items.
GLMMs are particularly suited for the present study as they are an extension of
multiple regression and thus follow the aim to predict categorical outcomes based
on predictor variables (fixed factors) and their interactions (cf. Bolker et al. 2009).
GLMMs also allow for the inclusion of random variables in the model to control for
effects that stem from either the language material included or speaker variance and
thus are able to avoid what has been labelled the ‘‘language-as-fixed-effect fallacy’’
(Clark 1973). As early as 1973, Clark (1973: 335) criticizes that researchers have all
too often generalized their findings ‘‘beyond the specific language materials they
Table 3 Subcorpora used in the present study
AmE: Subcorpus SBCSAE BrE: Subcorpus ICE-GB
Medium Spoken Spoken
Variety American English British English
Size 211,932 words 213,659 words
Sampling period 1990s 1990–1993
Discourse types Informal conversations: face-to-face
(96%), telephone (4%)
Informal conversations: face-to-face
(90%), telephone (10%)a
a In order to rule out influences of the different proportion of discourse type in the two subcorpora, the
distribution of response types and strategies is compared across the face-to-face and complete database.
The statistical testing reveals no significant differences between the face-to-face request responses and the
whole database in either variety (AmE: v2 (3) = 0.111, p[ 0.5; BrE: v2 (3) = 0.037, p[ 0.5). Thus we
conclude that the discourse type does not have a significant impact on the realization of the request
response. As the number of telephone request responses is too low in both subcorpora (AmE N = 6, BrE
N = 18), no statistical tests were run on those data
66 I. Flock, R. Geluykens
123
have chosen’’ and thus ignored the influence of variables like individual speakers on
the whole data set. In a similar vein, Manning (2007: 1) argues that ignoring random
effects by not modelling ‘‘the often significant correlation between data coming
Table 4 Coding scheme of request responses applied in the present study
Category Strategy Format Example
Compliance
Explicit Agreement Particle Yeah
Minimal clausal A: We should go soon B: We should
Unrelated clausal A: We can put a pillow over her
head.—B: It’s for her best
Indication of compliance Minimal clausal A: Make sure you don’t even have a
cup of coffee. B: I won’t
Expanded clausal A: You wanna open that or wait until
later? B: I’ll wait until later
Graded clausal A: Check it out. B: I’ll probably go
between coastal
Unrelated clausal A: You’ll have to [show a picture]. B: I
have one somewhere
Implicit Request for specification Unrelated clausal A: Cut me a slice there. B: This big?
Positive evaluation Unrelated clausal A: Let’s get away. B: I’d love to
Follow-up request Unrelated clausal A: Yeah, I noticed on the case for the
tape recorder too, that it’s all
covered today. Look right here. B:
Look at your cigarettes even
Delegating request Unrelated clausal A: Can we take this to the table? B:
Take everything to the table, C
Indication of postponing Unrelated clausal A: Put the rest in there. B: Just a
minute
Non-compliance
Explicit Disagreement Particle A: Would you turn on the light? B: No
Unrelated clausal A: Just shut up and listen to me. B: I
don’t think there is that much
Indication of non-compliance Minimal clausal A: Can’t you stand up and hold it? B: I
can’ta
Graded clausal A: Look it up. B: I can’t be bothered
Implicit Reason for non-compliance Unrelated clausal A: Aren’t you guys gonna stick up for
me? B: He’s bigger than I am
Challenge Unrelated clausal A: Turn em [hearing aids] up. B: Don’t
tell a great man what to do
Alternative action Unrelated clausal A: Do you want to go over X with me?
B: Actually, let’s go over Y
a The only examples of these strategies in the database are prefaced with a disagreement particle and are
counted as combination strategies in our analysis. They are listed without the particle for illustration
purposes here
Preference Organization and Cross-Cultural Variation… 67
123
from one speaker’’ can lead to underestimation of standard error estimates and thus
invalid significances.
We used two models for our analysis: While response type (compliance vs. non-
compliance) served as the dependent variable in the first model, response category
was used as the dependent variable in the second model. Possible fixed factors
included variety (AmE vs. BrE), directness of the request, response type and the
interaction between variety and response type. For random factors, participant and
item were selected. In order to arrive at the best model, we first started out with a
model that had a single random factor and then added additional random factors and
random slopes. The model fit in terms of inclusion of random effects and fixed
factors was assessed by comparing the Akaike-Information-Criterion values of fitted
models (AIC; Akaike 1998) using Likelihood ratio tests (utilizing the anova-
function). A decrease of two points in AIC values indicates a significant difference
between two minimally differing models. The generalized mixed effects models
were fitted with the Gauss-Hermite quadrature. We first contrast-coded the two
levels of response type and variety (-1 and ?1 for the two conditions) and the three
levels of request directness (-1, 0, ?1 for the three conditions) to allow for testing
the overall effect of the fixed factors. Additionally, we calculated the variety 9 re-
sponse category interaction in order to assess whether variety has a different impact
than response category.
In the end, the following models were established to have the best fit and were
thus selected for the analysis: In Model (1) response type (compliance vs. non-
compliance) served as the dependent variable and variety (AmE vs. BrE) and
directness of the request (as operationalized in three directness levels, cf.
‘‘Empirical Studies on Requests’’ section) were included as possible fixed factors.
In Model (2), response category (explicit vs. implicit) served as the dependent
variable with variety, response type, directness of the request and the interaction
between variety and response type as fixed factors. In both models, the random
factor of participant was included whereas item did not increase model fit.
Post-hoc comparisons on the levels of the interaction (in terms of the interaction
between variety and response type in Model 2) were carried out using the R-package
‘phia’ on the basis of multiple comparisons of factor contrasts (de Rosario-Martinez
2015). To adjust for multiple comparisons, the Holm–Bonferroni method was
applied. The Holm–Bonferroni correction reduces the possibility of obtaining
significant results (Type-I errors) when performing multiple tests.
Results
Response Types: Preference Organization
As a first rough estimation of preference organization, we have investigated the
relative frequencies of preferred (i.e. compliant) versus dispreferred (i.e. non-
compliant) responses in our database. Figure 1 shows the frequencies for both the
British and American data.
68 I. Flock, R. Geluykens
123
Not very surprisingly, in line with preference organization expectations and
Thompson et al.’s (2015) findings, the results show a clear preference for
compliance over non-compliance: over 70% of requests are complied with in both
data sets. While the frequency of compliance is slightly higher in the American than
in the British data (72.5 and 70.6%, respectively), the factor of variety does not have
a significant impact on the choice of response type (b = 0.07185, SE = 0.25738,
Z = 0.279, p = 0.7801). In other words, no cross-cultural variation is found with
regard to preference organization.
Things change slightly when one takes into account the response categories, i.e.
whether a response is uttered explicitly or implicitly (see Table 4 above). Explicit
responses signal (non-)compliance in a semantically unequivocal and transparent
manner. Signaling compliance explicitly can be achieved either through an explicit
agreement signal, as in (1), or through another overt and non-ambiguous compliance
signal, as in (2):
(1) MARILYN: .. Peter, would [you like to] … string the beans?
PETE: [What can I do]. Surea.a The transcription detail has been simplified in the examples.
Transcripts with (anonymized) participant names are taken from our
AmE subcorpus.
(2) B: Well make sure you don’t even have a cup of coffee before you set foot on it.
A: Well I won’t because it will weigh extra won’t it
Indicating non-compliance explicitly can likewise be done through the use of an
overt disagreement signal, as in (3), or another clear semantic indication of non-
compliance, as in (4):
72.5%(124)
70.6%(142)
27.5%(47)
29.4%(59)
0%
25%
50%
75%
100%
AmE responses BrE responses
Compliance Non-compliance
Fig. 1 Distribution of response types: compliance versus non-compliance
Preference Organization and Cross-Cultural Variation… 69
123
(3) MARLENA: Would you turn on the light?
KITTY: No,
MARLENA: … Why.
(4) A: Look it up
C: Triple the price
C: No I can’t be bothered
Implicit responses can be realized through a variety of different strategies (cf.
Table 4 above for an overview), What these strategies have in common is that there
is no clear, overt signal of (non-)compliance in the response; rather, the requester
has to work out whether the requestee is complying or not based on contextual cues
as well as on the response itself, through a conversational implicature. In example 5,
for instance, the requestee utters a request for further specification as a response to
the original request; in doing so, he implies that he is willing, in principle, to comply
with the request once this specification query is resolved:
(5) MARILYN: You could use the lettuce washer cause Pete’s using the colander.
ROY: .. Where’s the lettuce washer.
In example 6, the requestee implies non-compliance by giving the reason why
compliance will not be forthcoming; though there is no overt non-compliance signal
in the response, the requester should be (and as the example shows is indeed) able to
work out the dispreferred nature of the response through an implicature:
(6) A: Well do shut the door
B: He’s coming back
A: Yeah I know. But … sound travels
Politeness considerations would predict that non-compliant responses are preferably
done implicitly, since refusing to comply with a request constitutes a challenge to
the requester, which is a face-threatening act in its own right. Compliant responses,
on the other hand, do not constitute such a face threat, which should allow the
responder to formulate them in a fairly direct and explicit manner.
Figure 2 does indeed show a clear correlation between the type of response
(compliance vs. non-compliance) and the strategy type (explicit vs implicit)
employed. In both the British and the American data sets, non-compliant,
dispreferred responses are overwhelmingly realized through an implicit strategy
(87.2 and 93.2%, respectively), while preferred responses are most often realized
through an explicit response strategy.
This pattern does not apply to the same degree to both data sets: whereas British
responders overwhelmingly opt for an explicit strategy (86.6%), Americans do so to
a lesser extent (62.9%). In other words: American responders tend to opt more
frequently for an implicit strategy (37.1%) when complying with a request than their
British counterparts (13.4%). The statistical analysis reveals that the factor of
70 I. Flock, R. Geluykens
123
variety (AmE vs. BrE) (b = -3.7382, SE = 0.4341, Z = -8.612, p = 0.0001) and
its interaction with response type (compliance vs. non-compliance) (b = 2.3211,
SE = 0.2559, Z = 9.072, p = 0.0001) have a significant influence on the choice of
response category (explicit vs. implicit).4 The post hoc comparisons on two levels of
the interaction (AmE and BrE on compliance and AmE and BrE on non-
compliance) show that it is the influence of the compliance strategies that affect the
choice of response type significantly [compliance: v2 (1) = 15.7395, p\ 0.001;
non-compliance: v2 (1) = 0.8568, p[ 0.05]. We thus find significant cross-cultural
variation in the preference for explicit or implicit responses.
The results for our American speakers are somewhat in line with those found by
Thompson et al. (2015) for their American English data. The authors find that the
majority of their compliant responses are realized by particle, minimal and
expanded clausal responses (which roughly correspond to explicit compliant
responses) but also report that unrelated clausal responses (i.e. implicit strategies)
occur with some frequency.
Compliance Strategies and Their Linguistic Correlates
For our detailed analysis of the formal aspects of explicit compliance, we will
correlate our main explicit compliance strategies (agreement, indication of
compliance, or a combination of the two, cf. Table 4 in ‘‘Methodology’’ section)
with the response formats identified by Thompson et al. (2015) (cf. Table 2 in
62.9%(78)
86.6%(123)
12.8%(6)
6.8%(4)
37.1%(46)
13.4%(19)
87.2%(41) 93.2%
(55)
0%
25%
50%
75%
100%
AmE BrE AmE BrE
Explicit Implicit
Fig. 2 Distribution of response categories: explicit and implicit responses
4 The factors response type (b = -0.5347, SE = 1.1437, Z = 0.468, p = 0.6401) and directness of the
request (b = -0.1260, SE = 0.2395, Z = -0.526, p = 0.5988) did not have a significant effect on
response category.
Preference Organization and Cross-Cultural Variation… 71
123
‘‘Empirical Studies on Requests’’ section). Table 5 gives an overview of the explicit
strategies and their formal realization.
As we have seen in ‘‘Response Types: Preference Organization’’ section, explicit
compliance is significantly more frequent in British English (N = 123) than in
American English (N = 77). By far the most common strategy for explicitly
complying with a request is simple agreement, which is most frequently realized
through a single agreement particle in both data sets. Since no face work is
necessary for such second pair parts, this strategy provides the responder with the
most economical and transparent response option. For similar reasons, occurrences
of unrelated clausal strategies are relatively rare.
The type of agreement particle chosen is to some extent dependent on the variety
of English, as shown by Table 6 (which only shows those particles used in isolation,
i.e. not the ones used in combination with some other form of compliance).
By far the most common agreement token, generally speaking, is yeah: it is most
common in both British and American English, though slightly more so in the
former (38 vs. 33% of all particles, respectively). Next in line in terms of frequency
are yes (N = 20), okay/ok (N = 23), and mhm/mm (N = 18), which exhibit some
clear cross-cultural variation: while mhm/mm is used similarly in both varieties, yes
is almost exclusively used in British English, whereas okay/ok is typically used by
American speakers. All other particles occur relatively infrequently, though some
appear to be (almost) exclusive to one variety (e.g. right for British English, sure for
American English). Summing up, we can say that the choice of agreement particles
exhibits clear cross-cultural variation.
Table 5 Formats for explicit compliance strategies (following Thompson et al. 2015)
Strategy of explicit compliance Format AmE BrE
n % n %
Agreement Particle 61 93.8 90 91.8
Minimal clausal 0 0.0 2 2.0
Expanded clausal 1 1.5 0 0.0
Graded clausal 0 0.0 1 1.0
Unrelated clausal 3 4.6 5 5.1
Subtotal 65 100.0 98 100.0
Indication of compliance Minimal clausal 1 16.7 2 13.3
Expanded clausal 2 33.3 2 13.3
Graded clausal 1 16.7 6 40.0
Unrelated clausal 2 33.3 5 33.3
Subtotal 6 100.0 15 100.0
Agreement particle ? indication of compliance Minimal clausal 3 42.9 3 30.0
Expanded clausal 1 14.3 2 20.0
Graded clausal 1 14.3 4 40.0
Unrelated clausal 2 28.6 1 10.0
Subtotal 7 100.0 10 100.0
72 I. Flock, R. Geluykens
123
As we saw in ‘‘Response Types: Preference Organization’’ section, implicit
compliance is more frequent in our American data set. A closer look at the formal
realizations (again using Thompson et al.’s (2015) categories) of this implicit
compliance, and at its distribution over our various response categories (cf. Table 4
above) might shed some further light on its precise nature. Results can be found in
Table 7.
Table 7 shows, first of all, that all implicit compliance is realized through an
unrelated clausal format. It was established (in ‘‘Empirical Studies on Requests and
Their Responses’’ section) that such forms, with their relatively high degree of
agency, can be expected to occur after requests displaying weak deontic rights. This
certainly seems to be the case for some strategies. When a responder indicates he/
she wants to postpone the requested action, for instance, this is a clear signal that he/
she has a strong deontic right; similarly, an expression of positive evaluation implies
that the responder has a strong sense of entitlement, as he/she can afford to express
his/her positive feelings about the requested action (if requester entitlement is
strong, the responder’s evaluation of the request will be irrelevant).
Table 6 Agreement particles
used in the data setsAgreement particles AmE BrE
n % n %
yeah 20 32.8 34 37.8
yes 1 1.6 19 21.1
mhm/mm 8 13.1 10 11.1
right 1 1.6 7 7.8
combinations including yeah/yes 0 0.0 6 6.7
okay/ok 18 29.5 5 5.6
I know 2 3.3 4 4.4
sure 6 9.8 0 0.0
hm 3 4.9 0 0.0
Other 2 3.3 5 5.6
Total 61 100.0 90 100.0
Table 7 Formats for implicit compliance (following Thompson et al. 2015)
Strategy Format AmE BrE
n % n %
Request for specification (preparatory action) Unrelated clausal 38 82.6 17 89.5
Positive evaluation 4 8.7 2 10.5
Follow-up request 2 4.3 0 0
Delegating request 1 2.2 0 0
Indication of postponing 1 2.2 0 0
Subtotal 46 100 19 100
Preference Organization and Cross-Cultural Variation… 73
123
However, as can be seen in Table 7, the vast majority of implicit compliant
responses concern the strategy request for specification, in both data sets (83 and
89% of such responses, respectively). In these sequences, the responder counters the
request with a request for further specification; a form of preparatory action is thus
necessary for the successful carrying out of the initial request, as in:
(7) KEVIN: Cut me a slice there,
KENDRA: This big?
Such responses were categorized as indirectly compliant, by virtue of the fact that,
by asking for further specification, the responder implies his/her willingness to carry
out the request eventually, as soon as the trouble spot caused by the lack of
specification in the initial request is resolved (this interpretation is supported by
closer inspection of the further interaction, which usually confirms that the request
is complied with).
The implicit nature of the response, and its unrelated clausal format, in these
exchanges appears to be caused by a trouble spot (i.e. lack of sufficiently specific
information) in the immediate context of the request sequence, which needs to be
resolved before the (deferred) requested action can be carried out. In other words,
the successful completion of the request sequence is contingent on the resolution of
the trouble spot. It seems difficult here to claim that the responder has strong deontic
rights and that the speaker has a low level of entitlement; rather, the fact that the
responder requests further specification seems to indicate that the responder does
not question the deontic right of the speaker (i.e. his/her entitlement) to formulate
the request in the first place. What we appear to be dealing with here is a situation
with both high entitlement by the requester combined with high contingency. This
would seem to argue against the inverse correlation between entitlement and
contingency claimed by Thompson et al. (2015).
Non-compliance Strategies and Their Linguistic Correlates
Turning now to non-compliance, we have already established that this is mostly
realized implicitly. Explicit non-compliance is both strongly dispreferred and highly
face-threatening, and would indicate a strong sense of entitlement on the part of the
responder, i.e. a signal that the speaker has no right to request the action. Even so,
since non-compliance is dispreferred, one would expect the response to contain
some redressive action in order to minimize the face threat. Explicit responses,
especially those consisting only of a disagreement particle, would not be expected to
occur often as non-compliance signals; rather, they are the prototypical compliance
tokens, as shown in the previous section.
Table 8 does indeed show once again that explicit non-compliance (especially
realized through an isolated disagreement particle) is quite rare (10 out of 96
instances overall, or 10.4% of non-compliant responses). Only 4 instances of
isolated disagreement occur (none in the British data) and, interestingly, in 2 of
those cases the disagreement particle is in fact followed by a challenge of the
response by the original requester, as in:
74 I. Flock, R. Geluykens
123
(8) MARLENA: Would you turn on the light?
KITTY: No.
MARLENA: … Why.
In all other instances of non-compliance, the responder chooses to do so implicitly,
either by stating the reason for not wanting to comply with the request, as in
example 9, or by challenging the speaker’s right to formulate the request, as in 10:
(9) B: We should maybe just leave a message here saying head over
A: She won’t bother coming then though
(10) JO: .. Now you–Have you got your hearing aids [in].
WESS: [Ye]s dear.
JO: Well turn em up. … That’s enough.
WESS: Don’t tell a great man what to do.
In terms of Thompson et al.’s (2015) deontic rights analysis, these two implicit
strategies appear to be quite different. In challenging the speaker, the responder does
of course appear to indicate that the former does not have the deontic right, or
entitlement, to ask the addressee to carry out the requested action. Giving reasons
for non-compliance, on the other hand, cannot be interpreted simply in terms of lack
of the speaker’s deontic rights. While in some cases the reason for non-compliance
might make reference to the requester’s lack of entitlement (and hence the
responder’s deontic right to refuse to carry out the action), in other instances the
reason seems to have to do with the responder’s ability to carry out the request (i.e.
the epistemic dimension) or, more generally, the feasibility of the requested action.
In example 9, for instance, the responder appears to indicate that complying with the
request would be futile rather than to indicate that the requester is not entitled to ask
Table 8 Formats non-compliance strategies (following Thompson et al. 2015)
Strategy Format AmE BrE
n % n %
Explicit Disagreement particle Particle 4 66.7 0 0.0
Disagreement particle ? indication of non-
compliance
Minimal clausal 0 0.0 2 50.0
Graded clausal 0 0.0 1 25.0
Disagreement particle ? reason for non-
compliant
Unrelated clausal 2 33.3 0 0.0
Disagreement Unrelated clausal 0 0.0 1 25.0
Subtotal 6 100.0 4 100.0
Implicit Reason for non-compliance Unrelated clausal 24 58.5 39 70.9
Challenge Unrelated clausal 17 41.5 15 27.3
Alternative action Unrelated clausal 0 0.0 1 1.8
Subtotal 41 100.0 55 100.0
Preference Organization and Cross-Cultural Variation… 75
123
for the requested action. One could also formulate this, once again, purely in terms
of contingency: since the carrying out of the requested action is contingent on the
reason(s) mentioned in the implicit refusal, the degree of contingency is so high that
compliance is simply not an option (whether this is objectively the case is neither
here nor there; it is rather the responder’s estimation of the non-feasibility which is
the deciding factor here).
Overall, the detailed analysis of request response types, categories, strategies and
their linguistic correlates shows that correlating the functional and formal levels
yields results which might go unnoticed in a purely formal analysis. As we have
discussed both for implicit compliance and non-compliance strategies, functionally
diverse strategies (in terms of deontic rights) can be realized by unrelated clausal
formats. The inverse correlation between entitlement and contingency postulated by
Thompson et al. (2015) and its application to claims of agency in request sequences
thus appears to be an oversimplification.
Correlation Between Directness of the Request and Response Type
As a final step in the analysis, we have investigated whether there is any link
between the directness level of the request and the type of response it gets. Three
directness levels are differentiated here (cf. Table 1 in ‘‘Empirical Studies on
Requests and Their Responses’’ section): While directness level 1 (DL1) comprises
the most direct head acts, directness level 3 (DL3) includes off-record realizations
(hints). Directness level 2 (DL2) includes more indirect but still on-record
realizations.
This part of the investigation has two components. First of all, we need to check
whether directness levels have an influence on preference organization (Fig. 3). Put
differently: does the level of directness of the request decrease or increase the
likelihood of it being complied with? Figure 3 shows that (in-)directness (in contrast
to what Stivers and Rossano 2010 find) has no influence whatsoever on preference
organization: not only is compliance overall more frequent than non-compliance, it
is also equally frequent for both directness levels. The Likelihood ratio testing
revealed that leaving directness out of the model as a fixed factor to explain the
choice of response type increased model fit. Preference organization, it can be
concluded, is not influenced at all by the form of the request.
The statistical analysis further reveals that the directness level of the request does
not have an influence on the choice of response category in terms of explicitness/
implicitness. The Likelihood Ratio testing reveals that leaving directness and the
interaction between directness and variety as fixed factors out of the model
increased model fit. Entering directness as a single factor to the model did not show
significant influence of directness on the choice of response type, either
(b = 0.1358, SE = 0.1959, Z = 0.693, p = 0.488).
These findings are quite surprising as earlier studies (e.g. Stivers and Rossano
2010) predict that indirect requests would mobilize different kinds of responses.
This claim is clearly not supported by our analysis. As we have analyzed verbal
request responses only, we cannot say anything about the authors’ finding that
indirect requests are furthermore less likely to be responded to.
76 I. Flock, R. Geluykens
123
Discussion
Our empirical analysis has revealed some clear correlations between request
response format (compliance vs. non-compliance) and response type (explicit vs.
implicit). First of all, in line with preference organization expectations, compliant
responses are more likely to occur than non-compliant ones. Secondly, we have
shown that, while compliant responses are likely to be realized explicitly,
responders tend to non-comply in a more implicit manner. Given that non-
compliance is a dispreferred option, and that it results in increased face threat, this
also confirms our intuitions, and is in line with claims found in both the
conversation-analytic and politeness literature.
However, our AmE responses do not follow this pattern as clearly as the BrE data
in that American speakers comply significantly more often with requests in an
implicit manner than their British counterparts; they also tend to be slightly more
explicit when not complying. Apart from the deviance from preference structure
predictions in AmE, further differences occur on the lexical level in the choice of
agreement particle and in the individual strategies for realizing explicit and implicit
(non-) compliance. Furthermore, our analysis of co-occurrence patterns between
first and second pair part reveals that the form of the request does not appear to have
an impact on the choice of response strategy.
The relatively high number of implicit compliance strategies in our AmE
database is somewhat puzzling, and raises the question as to why responders would
feel the need to avoid explicitness in a response which appears to be non-face-
threatening (unlike non-compliance, which is intrinsically face-threatening). The
explanatory model offered for the high number of implicit compliance strategies by
Thompson et al. (2015), based on deontic rights, cannot fully account for the
66.7% (8)
67.9% (53)
73.0% (81)
66.7% (6)
72.1% (44)
73.3% (74)
33.3% (4)
32.1% (25)
27.0% (30)
33.3% (3)
27.9% (17)
26.7% (27)
0% 25% 50% 75% 100%
DL 3
DL 2
DL 1
DL 3
DL 2
DL 1
BrE
Am
ECompliance Non-compliance
Fig. 3 Co-occurrence patterns of response type and first pair directness level
Preference Organization and Cross-Cultural Variation… 77
123
patterns found in our data. As was shown in ‘‘Results’’ section, the majority of
implicitly compliant responses contain a request for specification. This indicates
that complying with the request is contingent on the resolution of a trouble spot,
rather than signaling low entitlement on the part of the speaker. Rather, the
requester does have a high degree of entitlement, but the request is also highly
contingent on other factors. Similarly, some non-compliant implicit responses
cannot be interpreted solely in terms of lack of entitlement by the requester; rather
they signal the responder’s inability to carry out the request (which may, again, be
due to some extraneous, non-deontic contingency).
Thompson et al.’s (2015) deontic rights approach is further unable to account for
our finding that the directness level of the first pair part does not have a significant
impact on the type and strategy chosen for the second pair part (cf. ‘‘Correlation
Between Directness of the Request and Response Type’’ section). A deontic rights
approach would predict that direct first pair parts (i.e. requests that display strong
deontic rights) should be more likely to be responded to with more implicit second
pair parts as they display weak deontic rights.
The present study has mainly made use of a functional coding scheme,
differentiating between response types (compliant vs non-compliant) and response
category (explicit vs implicit). This was compared to the formal coding
scheme employed by Thompson et al. (2015), which distinguishes between five
formally identifiable categories which in turns are presumed to correlate with
different levels of turn autonomy.
An examination of the similarities and differences between our functional
response categories and Thompson et al.’s (2015) formal categories reveals some
interesting results. First of all, as expected, the two coding schemes are congruent
for implicit responses, in that they are all realized as unrelated clausal responses. It
could hardly be otherwise, since all other categories in Thompson et al.’s (2015)
classification generate responses which, in our functional terms, would be labeled
explicit by definition.
The situation is different, however, for explicit responses. Thompson et al.’s
(2015) deontic rights approach would predict that low deontic rights are signaled
though the use of compliant responses with low turn autonomy and display of
agency (i.e. particle responses), while explicit non-compliance should be indicated
by forms displaying high turn autonomy (i.e. unrelated clausal responses). While in
our data the majority of explicit compliant responses are indeed realized
predominantly by particle forms (cf. Fig. 4), a significant portion are realized
through so-called graded and unrelated clausal strategies (see also Table 5).
According to Thompson et al. (2015), the latter two strategies are more autonomous
and display a higher degree of agency, and would thus not be predicted for explicitly
compliant responses, which should be associated with a display of lower deontic
rights.
In other words, in our data compliance may be signaled explicitly on a functional
level while employing a formally ‘indirect’ formulation such as an unrelated clause.
78 I. Flock, R. Geluykens
123
This is the case in example (11), where agreement is explicitly signaled through turn
completion:
(11) ANNETTE: We should just get one for both of our birthdays. Like maybe
[middle of the week]
ALICE: .. sometime during the week, for both of our birthdays-. Cause
I won’t be here for mine either.
The formal realization of the response here does not accurately reflect its functional
response category. Put differently: formal realizations alone are not a reliable
indicator of language functions (such as expressions of deontic rights). Moreover,
we have already argued, when discussing non-compliance (in ‘‘Non-compliance
Strategies and Their Linguistic Correlates’’ section), that deontic rights alone cannot
explain the choice for a particular response strategy.
The role of deontic rights in request sequences, and in particular the respective
impact of the notions of entitlement and contingency, certainly deserves further
investigation. This also holds true for claims made on the basis of deontic rights
about the influence of the first pair part on the second pair part. As empirical
research on the interaction between request and request response is scarce, it is
difficult to extrapolate from our present findings. More research on the interaction
between first and second pair parts (regardless of specific illocutions) is needed in
order to arrive at more robust generalizations.
78.2% 73.2%
5.1%5.7%
5.1%3.3%
2.6%8.9%
9.0% 8.9%
0%
25%
50%
75%
100%
AmE explicit compliance BrE explicit compliance
Unrelated clausalGraded clausalExpanded clausalMinimal clausalParticle
Fig. 4 Formal correlates of functional compliance response categories
Preference Organization and Cross-Cultural Variation… 79
123
Conclusion
To summarize, this paper has analyzed the functional and formal correlates of
request responses from a cross-cultural perspective. While most of our findings are
in line with expectations regarding preference organization and degree of
explicitness, some results run counter to expectations. For instance, a higher
number of implicit compliant responses was found than expected. We have argued
that a deontic rights approach, such as the one proposed by Thompson et al. (2015),
cannot fully account for such patterns. Other, non-deontic variables such as the
contingency of the response on the resolution of some inherent trouble spot play at
least a partial role.
In the present paper, we have employed a corpus-based approach with two (as we
have argued) maximally comparable subcorpora for our contrastive research design.
The corpus approach was specifically chosen in order to obtain enough request
sequences for qualitative and quantitative analyses. For some low-frequency
features, like indirect requestive first pair parts (i.e. hints), the numbers were still
very low. In our analysis of co-occurrence patterns, these sequences could thus not
be included systematically. This is unfortunate, as it is especially such low-
frequency features which may reveal patterns which might not show in the dataset
otherwise. In order to include such phenomena in a systematic analysis and still be
able to control for participant homogeneity, even larger spoken language corpora
would be needed that provide researchers with the detailed participant information
needed for sociolinguistic comparisons. As pragmatic phenomena more often than
not cannot be retrieved in automated searches, appropriate annotation systems such
as SPICE are needed in order to obtain sufficiently large databases for analysis. In
other words, much remains to be done in order to apply the advantages of a corpus
approach to the study of language use.
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